Event related potentials (ERPs) and alpha waves in cognition, aging and selected dementias: A source of biomarkers and therapy

Abstract

In 2010, 8% of the world’s population was >65 years of age. The prevalence of dementia in 2015 was 47.47 million, while its incidence was at 7.7 million new cases each year i.e. translates to a new case every 4.1 seconds. Alzheimer’s contributes to 60−70% of cases with dementia. The current global costs of care for dementia is US$ 604 billion/ year. One of the keep obstacles to better treatment outcomes and quality of life is late diagnosis. The present paper covers the role of EEG–based Alpha waves and event-related potential (ERPs) components as biomarkers of cognition and the changes in their features with aging, dementia, and Alzheimer’s. Introduction Normal aging and dementia Epidemiological studies on normal aging and dementia revealed that in 2010 there were 524 million individuals >65 years of age. This accounted for 8% of the world’s population in 2010. The projections for 2050 are that this number is expected to rise to 1.5 billion individuals >65 years and will account for 16% of the world’s projected population [1]. Further alarming statistic is that between 2010 and 2050, the number of older people in less developed countries will increase by 250% as compared with a 71% increase in developed countries [1]. Prevalence of dementia in 2015 was 47.47 million, with 75.63 million and 135.46 million being the projected estimated for 2030 and 2050 respectively [2-6]. Incidence of dementia is 7.7 million new cases each year i.e. translates to a new case every 4.1 seconds. 5%-8% of individuals > 65 age, 15%-20% > 75 age, and 25%-50% of individuals > 85 age have dementia. Alzheimer’s disease (AD) or senile dementia of the Alzheimer’s type (SDAT) contributes to 60−70% of cases with dementia [1-6]. The implications are that not only infrastructure in terms of health care systems and health care givers need to be up-scaled to meet future needs but that globally systems need to be set in place that can ensure we meet the cost of care. Factors influencing costs include; the cost of providing health and social care to the aged and individuals with dementia, effect on the work force in terms both care givers and younger individuals with early dementia and the effect on the family in terms of loss of income/reduction in income for both care givers and younger individuals with early dementia. Current global costs of caring for people with dementia are US$ 604 billion/ year and the projected global estimates is US$ trillion in 2050 [1-6]. Taken together one can appreciate the significant impact of dementia on the global population. *Correspondence to: Jonathan RT Lakey, Department of Surgery, 333 City Blvd West, Suite 1600, Orange, CA 92868, Tel:1-949-824-8022; Fax:1-714-456-6188; E-mail: jlakey@uci.edu Received: October 01, 2019; Accepted: October 17, 2019; Published: October 25, 2019 Electrophysiological studies on cognition While AD accounts for 60−70% of cases with dementia its clear-cut diagnosis from the other types of dementias namely; normal age-related dementia, frontotemporal lobar degeneration, vascular dementia, dementia with Lewy bodies, Parkinson’s disease dementia, CreutzfeldtJakob disease etc requires extensive and expensive clinical and neurological examination and testing [1-8]. Diagnosis and classification of dementia is based on the DSM-5 following a thorough neuro-clinical examination and neurophysiological testing using established tests like the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), the Clinical ,Dementia Rating Scale (CDRS), Ischemic Scale (HIS) and the Instrumental and Basic Activities of Daily Living (IADL, BADL) [9-15]. Individuals whose scores fall within -1 to -2 standard deviation (SD) range (between the 3rd and 16th percentiles) are diagnosed as having mild cognitive impairment and those with scores below -2SD or 3rd percentile major/severe cognitive impairment [9-15].These tests are either form-based or computer-based and may require either a clinician or trained technician and in some instances the patient themselves to fill out the test. The drawback of the tests is that a patient with early MCI may still be able to complete the test quite successfully and thus remained undiagnosed and untreated. One of the reasons attributed to failure of AD-modifying drugs has been that individuals are diagnosed in advanced stages of the disease [16-22]. In the search for a universal gold standard for diagnosis for Miranda P (2019) Event related potentials (ERPs) and alpha waves in cognition, aging and selected dementias: A source of biomarkers and therapy Volume 6: 2-12 Integr Mol Med, 2019 doi: 10.15761/IMM.1000385 AD several challenges still exist [16-22]. Cerebrospinal fluid (CSF) biomarkers include amyloid-beta (Aβ42) whose levels correspond to amyloid plaque levels in the brain and phosphorylated tau (p-Tau) are capable of differentiating AD dementia, MCI due to normal aging, and non-AD dementia [16-22]. Some of the drawbacks include; the tests are expensive and highly invasive, as CSF is obtained via a lumbar puncture [16-22]. In contrast the EEG is relatively inexpensive and electrophysiological biomarkers obtained from ERPs and brain waves (alpha, beta, theta, and gamma: frequency, amplitude, power etc) could possibly serve as screening and/or diagnostic tools depending on their sensitivity, specificity and accuracy [23]. Electrophysiology (EEG) based tests of cognition have the ability to pick up early changes in brain wave rhythms even prior to biochemical testing and neuroimaging [1-15]. Due to their cost, the duration and complexity of data interpretation and their cumbersome and temporal nature EEGs were earlier not popular as diagnostic tools. However developments in the field have resulted in more affordable, office-based and/or portable systems. Today’s EEG machines are capable of not only recording and evaluating brainwaves (alpha, beta, gamma, delta), evoked potentials and event related potentials (ERPs) but of quantifying and creating 2-D topographical color-coded brain maps comparing a patient’s brain function to a normative database via Quantitative EEG (QEEG), as well as using Low Resolution Electromagentic Tomography (LORETA) where 2-D EEG data is converted into 3-D data to source locate EEG waves down to the cortical areas/Brodmann Areas (BA) they originate from [24-26]. A key feature of normal aging, pre-senile and AD is neuro-cognitive impairment. The domains related to cognition as stipulated by DSM5 include: complex attention executive abilities learning/memory, language, visuoconstruction, visuoperception and social cognition [9]. EEG parameters pertinent to cognition include i) thalamic generated alpha waves (posterior alpha peak frequency) and ii) event related potentials (ERPs) components. These 1-D electrophysiological parameters are converted to 2-D QEEG maps to determine power, coherence and connectivity, 2-D data is then converted to 3-D data via source location of alpha waves or ERP’s using LORETA to locate the Brodmann areas (BA) involved is [23-26]. Event-related potentials (ERPs) and cognition Evoked or event-related potentials (ERPs) (Figures 1a-d) are obtained following an event/stimulus (visual, auditory, motor or task). Figure 1b, Figure 1c and Figure 1d shows the ERP components obtained using NeuralScan by Medeia, a state-of the-art computer-based EEG computer-based system. If for example, the neuro-electrophysiological test lasts 10-minutes and the stimuli is repeated every 30 seconds with a 10 second delay before the next cycle then each epoch that capture one complete stimuli and response cycle are marked out and selected during the EEG recording lasting 10-minutes. The averaged response gives the event-related potential (Figure 1b) for that stimulus. ERP’s obtained after resting-state EEG (eyes closed and opened, Figure 1c), or following a specific task to evaluate working memory or from evoked potentials (visual, auditory, odd ball paradigm) or following behavioral motor tests as used to assess the cognitive status. Table 1 provides a concise and comprehensive snapshot of the ERP components, the features pertinent to cognition that they reflect or are elicited by and their source location on the respective Brodmann areas (BA) [27-72]. Provided below are the pertinent definitions. ERP component – definitions [27-72]: • “P” and “N” denote the positive and negative nature of the ERP components. The number eg: P100 or N100 indicates the latency. • Peak amplitude: the difference between the mean prestimulus baseline and maximum peak amplitude. • Peak latency: the time point corresponding to the maximum amplitude and calculated relative to stimulus onset. • P50: defined as the maximum positivity between 24 and 72 ms poststimulus • P100: maximum negativity between 65 and 90 ms • N100: maximum negativity between 70 and 130 ms • P200 the maximum positivity between 180 and 235 ms (measured for standard and target), and • N200the maximum negativity between 205 and 315 ms (for target tones). • The P3a was defined as the maximum positivity between 325 and 500 ms (for the distractor), and the • P3b as the maximum positivity between 325 and 580 ms (for target tones). P3b amplitude is determined by the amount of attentional resources allocated when working memory is updated • Slow wave: maximum negativity between 460 and 680 ms (for target tones). Related to the P3b, or classic P300. It is elicited when a deviant stimulus is associated with a task and reflects an update in working memory. (Table 2) Event-Related potentials (ERPs) and cognitive impairment in normal aging and dementia P50 is generated by the primary and secondary auditory cortices [73]. It is an exogenous cognitive process [74]. It exhibits sensory gating at early sensory stage [75]. Its amplitude is modulated by frontal brain regions thus unrestrained P50 amplitudes as seen in AD are thought to indicate functional disconnection of the prefrontal cortex i.e. it