# Use of Covariance Analysis in Electroencephalogram Reveals Abnormalities in Parkinson's Disease
## 1 Introduction  
The diagnosis of PD is mainly clinically based on the presence of cardinal motor symptoms. There are no tests to provide an early-stage diagnosis of the disease. Currently, an accurate diagnosis can only be achieved conducting post-mortem pathological examinations [1]. Several techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), are helpful in confirming PD and rule out possible brain injury [2, 3]. Nevertheless, these medical examinations are not extensively available for several reasons: they can be costly, invasive, keep patients for prolonged periods in positions that are uncomfortable or stressful and cannot be prescribed to all patients. Therefore, it is necessary to generate new medical tools to confirm the clinical diagnosis of PD and research new biomarkers that help in the early identification of premotor expressions of the disease. These new tools must be low cost, accessible, less stressful, and even remotely possible. Parkinson's disease (PD) is a progressive neurodegenerative disorder that involves motor and non-motor symptoms. Major motor symptoms generally occur unilaterally and can include tremor, rigidity, and bradykinesia [1]. It has been observed that motor symptoms emerge later in women but with a faster progression and higher propensity to postural instability than men [4]. Non-motor symptoms typically appear before motor disorders and are the first symptoms of the disease. They include depression, anxiety, sleep disturbances and cognitive impairment [5; 6; 7]. In agreement with the Non-Motor Symptoms Scale, women are the population with more compromise on the sleep/fatigue and mood/cognition functions [8]. Currently, PD is the second most common neurodegenerative disorder in the world, affecting between 4 and 5 million people over 50 years of age worldwide [1]. Aging is the main risk factor of PD [9; 10] with a reported male to female incidence rate of 3:2 worldwide [11]. However, female incidence could increase in the coming years due to the longer life expectancy of women worldwide, as revealed by epidemiological studies [12]. Although there are several pieces of evidence relating PD to specific protein mutations, mainly the A53T mutation in the alpha-Synuclein protein [1; 13; 14], which occurs in less than 10% of the PD diagnosed. Most PD cases have a sporadic origin, and yet, their etiology and anatomical initiation remain to be uncovered. Pathophysiology of PD emphasizes that the motor and non-motor symptoms are related to abnormal neuronal firing rates or segregation/synchronization of neurons from specific circuits and loops between basal ganglia, thalamus, limbic areas, and specific cortical lobes [15], which may be analyzed through electroencephalography. Electroencephalography monitors neural activity of the cerebral cortex in real time with high temporal resolution [16] providing dynamic information on the electrical brain activity and connectivity. Quantitative electroencephalography has been used to detect abnormalities in brain activity and identify cognitive impairment in early stages of PD [17; 18]. In agreement with the above-mentioned information, differences in the power of brainwaves, \(\delta\) (0-4 Hz), \(\theta\) (4-8 Hz), \(\alpha\) (8-13 Hz) and \(\beta\) (13-30 Hz), from PD patients have been described; for instance, increases in \(\delta\) and \(\theta\) brainwaves and decreases in \(\alpha\) and \(\beta\) brainwaves [19]. On the other hand, imbalances in \(\beta\) and \(\gamma\) brainwaves have also been identified and associated with the motor symptoms of the disease [20]. Therefore, EEG analyses have been considered a reliable biomarker for PD with greater sensitivity and pattern specificity [21; 22]. Since EEG contains non-linear features, it is necessary to use new analytical methodologies to reveal more information related to brain abnormalities, which could still be hidden. Wavelet analyses are spectral tools used in medicine and biology for diagnosis and tracing.