The pedunculopontine nucleus (PPN) is situated in the upper pons in the dorsolateral portion of the ponto-mesencephalic tegmentum. Its main mass is positioned at the trochlear nucleus level, and is part of the mesenphalic locomotor region (MLR) in the upper brainstem. The human PPN is divided into two subnuclei, the pars compacta (PPNc) and pars dissipatus (PPNd), and constitutes both cholinergic and non-cholinergic neurons with afferent and efferent projections to the cerebral cortex, thalamus, basal ganglia (BG), cerebellum, and spinal cord. The BG controls locomotion and posture via GABAergic output of the substantia nigra pars reticulate (SNr). In PD patients, GABAergic BG output levels are abnormally increased, and gait disturbances are produced via abnormal increases in SNr-induced inhibition of the MLR. Since the PPN is vastly connected with the BG and the brainstem, dysfunction within these systems lead to advanced symptomatic progression in Parkinson's disease (PD), including sleep and cognitive issues. To date, the best treatment is to perform deep brain stimulation (DBS) on PD patients as outcomes have shown positive effects in ameliorating the debilitating symptoms of this disease by treating pathological circuitries within the parkinsonian brain. It is therefore important to address the challenges and develop this procedure to improve the quality of life of PD patients.

Sleep is an indispensable normal physiology of the human body fundamental for healthy functioning. It has been observed that Parkinson's disease (PD) not only exhibits motor symptoms, but also non-motor symptoms such as metabolic irregularities, altered olfaction, cardiovascular dysfunction, gastrointestinal complications and especially sleep disorders which is the focus of this review. A good understanding and knowledge of the different brain structures involved and how they function in the development of sleep disorders should be well comprehended in order to treat and alleviate these symptoms and enhance quality of life for PD patients. Therefore it is vital that the normal functioning of the body in relation to sleep is well understood before proceeding on to the pathophysiology of PD correlating to its symptoms. Suitable treatment can then be administered toward enhancing the quality of life of these patients, perhaps even discovering the cause for this disease.

Electroencephalography (EEG) can reveal the abnormalities of dopaminergic subcortico-cortical circuits in patients with Parkinson’s disease (PD). However, conventional time-frequency analysis of EEG signals cannot fully reveal the non-linear processes of neural activities and interactions. A novel Holo-Hilbert Spectral Analysis (HHSA) was applied to reveal non-linear features of resting state EEG in 99 PD patients and 59 healthy controls (HCs). PD patients demonstrated a reduction of β bands in frontal and central regions, and reduction of γ bands in central, parietal, and temporal regions. Compared with early-stage PD patients, late-stage PD patients demonstrated reduction of β bands in the posterior central region, and increased θ and δ2 bands in the left parietal region. θ and β bands in all brain regions were positively correlated with Hamilton depression rating scale scores. Machine learning algorithms using three prioritized HHSA features demonstrated “Bag” with the best accuracy of 0.90, followed by “LogitBoost” with an accuracy of 0.89. Our findings strengthen the application of HHSA to reveal high-dimensional frequency features in EEG signals of PD patients. The EEG characteristics extracted by HHSA are important markers for the identification of depression severity and diagnosis of PD.