Elsevier

Neurobiology of Aging

Volume 91, July 2020, Pages 88-111
Neurobiology of Aging

Regular article
Abnormal cortical neural synchronization mechanisms in quiet wakefulness are related to motor deficits, cognitive symptoms, and visual hallucinations in Parkinson's disease patients: an electroencephalographic study

https://doi.org/10.1016/j.neurobiolaging.2020.02.029Get rights and content

Highlights

  • In Parkinson's disease patients, resting-state delta and alpha electroencephalographic source activities were abnormal.

  • Those abnormalities were differently related to cognitive, motor, and perceptual deficits.

  • Those source activities may reflect the effect of Parkinson's disease on cognitive, motor, and perceptual systems.

Abstract

Compared with Alzheimer's disease (AD), Parkinson's disease (PD) shows peculiar clinical manifestations related to vigilance (i.e., executive cognitive deficits and visual hallucinations) that may be reflected in resting-state electroencephalographic rhythms. To test this hypothesis, clinical and resting-state electroencephalographic rhythms in age-, sex-, and education-matched PD patients (N = 136) and Alzheimer's disease patients (AD, N = 85), and healthy older participants (Nold, N = 65), were available from an international archive. Electroencephalographic sources were estimated by eLORETA software. The results are as follows: (1) compared to the Nold participants, the AD and PD patients showed higher widespread delta source activities (PD > AD) and lower posterior alpha source activities (AD > PD); (2) the PD patients with the most pronounced motor deficits exhibited very low alpha source activities in widespread cortical regions; (3) the PD patients with the strongest cognitive deficits showed higher alpha source activities in widespread cortical regions; and (4) compared to the PD patients without visual hallucinations, those with visual hallucinations were characterized by higher posterior alpha sources activities. These results suggest that in PD patients resting in quiet wakefulness, abnormalities in cortical neural synchronization at alpha frequencies are differently related to cognitive, motor, and visual hallucinations. Interestingly, parallel PD neuropathological processes may have opposite effects on cortical neural synchronization mechanisms generating cortical alpha rhythms in quiet wakefulness.

Introduction

It is well known that Parkinson's disease (PD) presents abnormalities in frontal executive and motor functions, owing to the progressive neurodegeneration by nigrostriatal dopaminergic neurons about intracellular Lewy bodies and neurofibrillary tangles (Parkkinen et al., 2008). During the PD progression, this core neurodegenerative process of the motor systems impairs related frontostriatal, mesocortical, mesolimbic, and frontoparietal neural networks, which are modulated by dopaminergic, cholinergic, serotonergic, and noradrenergic neurotransmitters (Buddhala et al., 2015, Gratwicke et al., 2015, Joutsa et al., 2015, Stahl, 2016). As a result, PD clinical manifestations extend to visual hallucinations, disorders of vigilance and sleep, and fluctuations of cognitive functions (Aarsland et al., 2003, Buter et al., 2008, Emre, 2003, Hughes et al., 2000, Levy et al., 2000, Muslimovic et al., 2005). In particular, visual hallucinations are very frequent (>50%) in PD patients with dementia (PDD, Fénelon et al., 2000, Nomura et al., 2003, Nishio et al., 2018).

Unfortunately, the mentioned clinical phenotype of the PD partially overlaps with that of other neurodegenerative dementing disorders such as dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), so the clinical practice in many millions of PD, DLB, and AD patients would benefit of biomarkers that are noninvasive, cost-effective, repeatable over time, and largely accessible worldwide. For ideal precision medicine, these biomarkers should be sensitive to different brain neural substrates underpinning these neuropathological clinical manifestations.

Among various candidates, biomarkers derived from the spectral analysis of resting-state eyes-closed electroencephalographic (rsEEG) rhythms theoretically show all the desired characteristics. In the study of human brain functions, resting-state eyes-closed condition is typically defined as a behavioral mode unrelated to visual/auditory information processing and motor or goal-oriented cognitive operations (e.g., oriented thinking, problem-solving, expectancy, planning daily activities, and so forth). As such, this condition allows the investigation of neurophysiological thalamocortical and corticothalamic neural synchronization mechanisms underpinning the generation of rsEEG activity and the regulation of low levels of vigilance in the quiet wakefulness. Of note, a proper level of vigilance is important for the efficiency of basic cognitive processes such as focused attention, the encoding and retrieval of memorized information, and executive and motor functions directing human behaviors. In this line, previous studies have unveiled significant relationships between the magnitude and topography of rsEEG rhythms recorded in quiet wakefulness and both spatial-temporal evolution of electroencephalographic (EEG) activity related to sensory and cognitive-motor events as amplitude and latency of event-related EEG potential peaks and dynamic changes in power in delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), and gamma (>30 Hz) oscillations (Babiloni et al., 2006a, Babiloni et al., 2006b, Polich, 1997). For example, it has been reported a relationship between power of posterior resting state alpha rhythms and the amplitude of late positive component of event-related potentials (i.e., P3) related to rare stimuli (i.e., oddball paradigm; Polich, 1997) and (visual primary visual consciousness (Babiloni et al., 2006a, Babiloni et al., 2006b). Furthermore, larger P3 amplitudes were related to more efficient resting-state brain networks as revealed by Graph Theory indexes derived from rsEEG rhythms (Li et al., 2015).

Several previous studies have shown rsEEG rhythms in PD patients (Bonanni et al., 2008, Bosboom et al., 2006, Bosboom et al., 2009, Caviness et al., 2016, Fünfgeld, 1995, Kamei et al., 2010, Melgari et al., 2014, Pugnetti et al., 2010, Serizawa et al., 2008). Results have shown that when compared to healthy older participants (Nold), PD patients with cognitive deficits were characterized by higher rsEEG power at delta (<4 Hz) and theta (4–7 Hz) rhythms in topographically widespread cortical regions, associated with a reduction of alpha (8–12 Hz) power (Bonanni et al., 2008, Bosboom et al., 2006, Bosboom et al., 2009, Caviness et al., 2016, Fünfgeld, 1995, Kamei et al., 2010, Melgari et al., 2014, Pugnetti et al., 2010, Serizawa et al., 2008). Compared to PD patients with intact cognition, PD patients with cognitive deficits exhibited lower frequency in the alpha power peak, greater global theta and delta power over the whole scalp, and lower power at alpha and beta (13–30 Hz) frequency bands (Caviness et al., 2007, Caviness et al., 2016).

To enhance the spatial and frequency details of the aforementioned rsEEG results, our Consortium used a methodological approach including (1) the estimation of rsEEG cortical sources by the popular exact low-resolution brain electromagnetic tomography (eLORETA) freeware (Pascual-Marqui, 2007) and (2) the definition of delta, theta, and alpha frequency bands on an individual basis using the so-called individual alpha frequency (IAF) peak as a reference in the rsEEG power density spectrum averaged across all electrodes (Klimesch et al., 1996, Klimesch et al., 1998, Klimesch, 1999). This individual analysis of alpha rhythms is of particular importance as the lower the rsEEG power at the alpha frequencies, the higher the general cortical arousal in both resting-state and cognitive-motor events (Pfurtscheller and Lopes da Silva, 1999). Furthermore, previous evidence led support to the thesis that the IAF allows disentangling two main components of brain forebrain and thalamus-cortical neurophysiological mechanisms underlying low- (e.g., alpha 1 and 2) and high-frequency (e.g., alpha 3) alpha rhythms in the resting-state condition. In this theoretical framework, low-frequency alpha rhythms may reflect brain neural networks underpinning general brain arousal, whereas high-frequency alpha rhythms may reflect those underpinning attention, memory, and other higher functions (Klimesch et al., 1996, Klimesch et al., 1998, Klimesch, 1999).

The present retrospective study reanalyzed the rsEEG database used to test different hypotheses in three reference investigations carried out by our international consortium using the same methodological approach (Babiloni et al., 2017a, Babiloni et al., 2017b, Babiloni et al., 2019). In the first reference investigation (Babiloni et al., 2017a), we introduced the eLORETA source estimation of rsEEG rhythms using individual frequency bands from delta to gamma in the comparison among groups of old participants with intact cognition (Nold) and patients with dementia due to AD, PD, and LBD. Results showed that compared with the Nold seniors, the AD patients were characterized by more abnormalities in posterior alpha (8–10 Hz) source activities, while PD patients exhibited more abnormalities in widespread delta (2–4 Hz) source activities. Compared with the AD and PD patients, the LBD patients showed intermediate abnormalities in delta and alpha source activities.

In the second reference investigation (Babiloni et al., 2017b), the aforementioned spatial patterns of delta and alpha source abnormalities were confirmed in the PD patients with mild cognitive impairment (PDMCI) about ADMCI patients and Nold participants.

In the third reference investigation (Babiloni et al., 2019), an acute dose of levodopa enhancing motor functions in PD patients induced a decrease in both widespread delta and alpha source activities. Furthermore, posterior alpha source activities were greater in PD patients with cognitive deficits over those with relatively intact cognition (Babiloni et al., 2019).

Keeping in mind those results, it can be speculated that (1) in AD, reduced cholinergic neurotransmission might strongly depress posterior alpha rhythms in brain cognitive systems about the severity of clinical symptoms (Babiloni et al., 2017a, Babiloni et al., 2017b); (2) In PD, reduced dopaminergic neurotransmission might moderately depress posterior alpha rhythms in brain motor systems and slightly enhance them in cognitive systems (Babiloni et al., 2019). In this speculative line, cholinergic and dopaminergic neurotransmissions might have opposite effects on posterior alpha source activities and cognitive systems (Babiloni et al., 2019). Furthermore, abnormalities in posterior alpha source activities underlying cognitive systems (e.g., visual attention and perception) might be related to visual hallucinations in PD, a significant clinical manifestation in that disease (Prell, 2018, Yao et al., 2015). Unfortunately, the mentioned previous reference investigations did not test those predictions.

The present retrospective study reanalyzed the EEG and clinical databases of the three reference investigations (Babiloni et al., 2017a, Babiloni et al., 2017b, Babiloni et al., 2019) to test the (new) original hypothesis that cortical sources of posterior alpha rhythms may be more active not only in PD patients with greater cognitive symptoms but also in those with visual hallucinations, as a possible effect of an impairment in dopaminergic neurotransmission. To test this original hypothesis, the experimental design compared cortical sources of rsEEG rhythms in age-, sex-, and education-matched PD, AD, and Nold seniors. In the experimental design, cortical rsEEG sources estimated in Nold participants represented the norm, while those assessed in AD patients allowed the evaluation of the specificity of abnormalities in rsEEG cortical sources computed in PD patients. We assumed that abnormalities in posterior alpha source activities might be mainly due to an impairment in dopaminergic systems in PD patients and cholinergic systems in AD patients. In the experimental design, PD patients with lower versus greater motor and cognitive systems were contrasted to assess the effects of these clinical features on rsEEG source activities. In the same line, PD patients with visual hallucinations were contrasted with those without this clinical feature.

Section snippets

Participants

In the present exploratory and observational study, clinical and rsEEG data were taken from an international archive formed by the Clinical Units of the PDWAIVE and E-DLB Consortia. Specifically, the PD group (N = 136) was formed by 36 PDD patients, 58 PDMCI, and 42 PD patients with normal global cognition (PDNC). Age-, sex-, and education-matched groups of AD patients (N = 85) and Nold participants (N = 65) were also taken from the same archive for control purposes. In detail, the AD group was

Statistical comparison of the rsEEG source activities in the Nold, AD, and PD groups

The mean TF was 5.9 Hz (±0.1 SE) in the Nold group, 5.5 Hz (±0.1 SE) in the AD group, and 5.2 Hz (±0.1 SE) in the PD group. Furthermore, the mean IAF was 9.2 Hz (±0.1 SE) in the Nold group, 8.6 Hz (±0.2 SE) in the AD group, and 7.8 Hz (±0.1 SE) in the PD group. The ANOVAs using these values as an input showed the following statistically significant findings: (1) the mean TF was greater (F = 11.1, p < 0.00005) in the Nold than the AD (p < 0.01) and PD (p < 0.00001) groups as well as in the AD

Discussion

In the present retrospective study, we hypothesized that cortical sources of eyes-closed rsEEG rhythms at delta and alpha frequencies may differ as a function of relevant clinical features in PD patients such as the severity of motor and cognitive deficits and the presence of visual hallucinations. The hypothesis of the study was evaluated by comparing rsEEG source activities estimated between matched PD groups with different clinical symptoms. In this framework, the cortical sources of delta

Methodological remarks

In the present retrospective study, we used the same general methodology and EEG/clinical databases of three previous reference investigations (Babiloni et al., 2017a, Babiloni et al., 2017b, Babiloni et al., 2019). In the neurophysiological and clinical interpretation of the results, some significant methodological limitations of the study should be taken into account.

Here the data collection was performed without unique instrumental recordings and clinical protocols within the consortium. For

Conclusions

In this retrospective study, we tested the hypothesis that (eLORETA) cortical sources of rsEEG rhythms may differ in PD patients as a function of relevant clinical variables such as motor symptoms, cognitive deficits, and visual hallucinations, mostly related to a significant impairment in dopaminergic ascending systems. For this purpose, AD patients were used as a pathological control group possibly characterized by a significant impairment in ascending cholinergic systems.

As a novelty with

Disclosure statement

The authors have no actual or potential conflicts of interest.

CRediT authorship contribution statement

Claudio Babiloni: Conceptualization, Methodology, Writing - original draft. Maria Teresa Pascarelli: Conceptualization, Methodology, Data curation, Formal analysis, Writing - original draft. Roberta Lizio: Conceptualization, Methodology, Data curation, Writing - original draft. Giuseppe Noce: Data curation, Formal analysis, Writing - original draft. Susanna Lopez: Data curation, Formal analysis, Writing - original draft. Marco Rizzo: Formal analysis, Data curation. Raffaele Ferri: Funding

Acknowledgements

The present study was developed based on the data of the informal European Consortium PDWAVES and European Consortium of Dementia with Lewy Body. The members and institutional affiliations of the Consortia are reported in the cover page of this manuscript. In this study, the electroencephalographic data analysis was partially supported by the funds of “Ricerca Corrente” attributed by Italian Ministry of Health to the IRCCS SDN of Naples, IRCCS OASI of Troina, and IRCCS San Raffaele Pisana of

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