Altered alpha and theta oscillations correlate with sequential working memory in Parkinson’s disease

Disrupted sleep-wake regulation in the MCI-Park mouse model of Parkinson's disease

Disrupted sleep has a profound adverse impact on lives of Parkinson's disease (PD) patients and their caregivers. Sleep disturbances are exceedingly common in PD, with substantial heterogeneity in type, timing, and severity. Among the most common sleep-related symptoms reported by PD patients are insomnia, excessive daytime sleepiness, and sleep fragmentation, characterized by interruptions and decreased continuity of sleep. Alterations in brain wave activity, as measured on the electroencephalogram (EEG), also occur in PD, with changes in the pattern and relative contributions of different frequency bands of the EEG spectrum to overall EEG activity in different vigilance states consistently observed. The mechanisms underlying these PD-associated sleep-wake abnormalities are poorly understood, and they are ineffectively treated by conventional PD therapies. To help fill this gap in knowledge, a new progressive model of PD - the MCI-Park mouse - was studied. Near the transition to the parkinsonian state, these mice exhibited significantly altered sleep-wake regulation, including increased wakefulness, decreased non-rapid eye movement (NREM) sleep, increased sleep fragmentation, reduced rapid eye movement (REM) sleep, and altered EEG activity patterns. These sleep-wake abnormalities resemble those identified in PD patients. Thus, this model may help elucidate the circuit mechanisms underlying sleep disruption in PD and identify targets for novel therapeutic approaches.

Cross-frequency and inter-regional phase synchronization in explicit transitive inference

Explicit logical reasoning, like transitive inference, is a hallmark of human intelligence. This study investigated cortical oscillations and their interactions in transitive inference with EEG. Participants viewed premises describing abstract relations among items. They accurately recalled the relationship between old pairs of items, effectively inferred the relationship between new pairs of items, and discriminated between true and false relationships for new pairs. First, theta (4-7 Hz) and alpha oscillations (8-15 Hz) had distinct functional roles. Frontal theta oscillations distinguished between new and old pairs, reflecting the inference of new information. Parietal alpha oscillations changed with serial position and symbolic distance of the pairs, representing the underlying relational structure. Frontal alpha oscillations distinguished between true and false pairs, linking the new information with the underlying relational structure. Second, theta and alpha oscillations interacted through cross-frequency and inter-regional phase synchronization. Frontal theta-alpha 1:2 phase locking appeared to coordinate spectrally diverse neural activity, enhanced for new versus old pairs and true versus false pairs. Alpha-band frontal-parietal phase coherence appeared to coordinate anatomically distributed neural activity, enhanced for new versus old pairs and false versus true pairs. It suggests that cross-frequency and inter-regional phase synchronization among theta and alpha oscillations supports human transitive inference.

Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease

Cognitive impairment is the most frequent non-motor symptom in Parkinson's disease and is associated with deficits in a number of cognitive functions including working memory. However, the pathophysiology of Parkinson's disease cognitive impairment is poorly understood. Beta oscillations have previously been shown to play an important role in cognitive functions including working memory encoding. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits increases the spectral power of beta oscillations and results in Parkinson's disease motor symptoms. Analogous changes in parallel cognitive CSTC circuits involving the caudate and dorsolateral prefrontal cortex (DLPFC) may contribute to Parkinson's disease cognitive impairment. The objective of our study is to evaluate whether changes in beta oscillations in the caudate and DLPFC contribute to cognitive impairment in Parkinson's disease patients. To investigate this, we used local field potential recordings during deep brain stimulation surgery in 15 patients with Parkinson's disease. Local field potentials were recorded from DLPFC and caudate at rest and during a working memory task. We examined changes in beta oscillatory power during the working memory task as well as the relationship of beta oscillatory activity to preoperative cognitive status, as determined from neuropsychological testing results. We additionally conducted exploratory analyses on the relationship between cognitive impairment and task-based changes in spectral power in additional frequency bands. Spectral power of beta oscillations decreased in both DLPFC and caudate during working memory encoding and increased in these structures during feedback. Subjects with cognitive impairment had smaller decreases in caudate and DLPFC beta oscillatory power during encoding. In our exploratory analysis, we found that similar differences occurred in alpha frequencies in caudate and theta and alpha in DLPFC. Our findings suggest that oscillatory power changes in cognitive CSTC circuits may contribute to cognitive symptoms in patients with Parkinson's disease. These findings may inform the future development of novel neuromodulatory treatments for cognitive impairment in Parkinson's disease.

Translating Pathological Brain Activity Primers in Parkinson's Disease Research

Translational experimental approaches that help us better trace Parkinson's disease (PD) pathophysiological mechanisms leading to new therapeutic targets are urgently needed. In this article, we review recent experimental and clinical studies addressing abnormal neuronal activity and pathological network oscillations, as well as their underlying mechanisms and modulation. Our aim is to enhance our knowledge about the progression of Parkinson's disease pathology and the timing of its symptom's manifestation. Here, we present mechanistic insights relevant for the generation of aberrant oscillatory activity within the cortico-basal ganglia circuits. We summarize recent achievements extrapolated from available PD animal models, discuss their advantages and limitations, debate on their differential applicability, and suggest approaches for transferring knowledge on disease pathology into future research and clinical applications.

Aberrant neural processing of event boundaries in persons with Parkinson's disease

The perception of everyday events implies the segmentation into discrete sub-events (i.e. event segmentation). This process is relevant for the prediction of upcoming events and for the recall of recent activities. It is thought to involve dopaminergic networks which are strongly compromised in Parkinson's disease (PD). Indeed, deficits of event segmentation have been previously shown in PD, but underlying neuronal mechanisms remain unknown. We therefore investigated 22 persons with PD and 22 age-matched healthy controls, who performed an event segmentation task with simultaneous electroencephalography (EEG). Both groups had to indicate by button press the beginning of sub-events within three movies showing persons performing everyday activities. The segmentation performance of persons with PD deviated significantly from that of controls. Neurophysiologically, persons with PD expressed reduced theta (4-7 Hz) activity around identified event boundaries compared to healthy controls. Together, these results point to disturbed event processing in PD. According to functions attributed to EEG activities in particular frequency ranges, the PD-related theta reduction could reflect impaired matching of perceptual input with stored event representations and decreased updating processes of event information in working memory and, thus, event boundary identification.

EEG-Based Mapping of Resting-State Functional Brain Networks in Patients with Parkinson's Disease

(1) Background: Directed functional connectivity (DFC) alterations within brain networks are described using fMRI. EEG has been scarcely used. We aimed to explore changes in DFC in the sensory-motor network (SMN), ventral-attention network (VAN), dorsal-attention network (DAN), and central-executive network (CEN) using an EEG-based mapping between PD patients and healthy controls (HCs). (2) Methods: Four-minutes resting EEG was recorded from 29 PD patients and 28 HCs. Network’s hubs were defined using fMRI-based binary masks and their electrical activity was calculated using the LORETA. DFC between each network’s hub-pairs was calculated for theta, alpha and beta bands using temporal partial directed coherence (tPDC). (3) Results: tPDCs percent was lower in the CEN and DAN in PD patients compared to HCs, while no differences were observed in the SMN and VAN (group*network: F = 5.943, p < 0.001) in all bands (group*band: F = 0.914, p = 0.401). However, in the VAN, PD patients showed greater tPDCs strength compared to HCs (p < 0.001). (4) Conclusions: Our results demonstrated reduced connectivity in the CEN and DAN, and increased connectivity in the VAN in PD patients. These results indicate a complex pattern of DFC alteration within major brain networks, reflecting the co-occurrence of impairment and compensatory mechanisms processes taking place in PD.

EEG Evaluation in a Neuropsychological Intervention Program Based on Virtual Reality in Adults with Parkinson's Disease

Nowadays, several strategies for treating neuropsychologic function loss in Parkinson’s disease (PD) have been proposed, such as physical activity performance and developing games to exercise the mind. However, few studies illustrate the incidence of these therapies in neuronal activity. This work aims to study the feasibility of a virtual reality-based program oriented to the cognitive functions’ rehabilitation of PD patients. For this, the study was divided into intervention with the program, acquisition of signals, data processing, and results analysis. The alpha and beta bands’ power behavior was determined by evaluating the electroencephalography (EEG) signals obtained during the execution of control tests and games of the “Hand Physics Lab” Software, from which five games related to attention, planning, and sequencing, concentration, and coordination were taken. Results showed the characteristic performance of the cerebral bands during resting states and activity states. In addition, it was determined that the beta band increased its activity in all the cerebral lobes in all the tested games (p-value < 0.05). On the contrary, just one game exhibited an adequate performance of the alpha band activity of the temporal and frontal lobes (p-value < 0.02). Furthermore, the visual attention and the capacity to process and interpret the information given by the surroundings was favored during the execution of trials (p-value < 0.05); thus, the efficacy of the virtual reality program to recover cognitive functions was verified. The study highlights implementing new technologies to rehabilitate people with neurodegenerative diseases.