Editorial: Early indicators of cognitive decline, Alzheimer's disease, and related dementias captured by neurophysiological tools

Highlights • The COVID-19 pandemic is causing global morbidity and mortality, straining health systems, and disrupting society, putting individuals with Alzheimer's disease and related dementias (ADRD) at risk of significant harm. • In this Special Article, we examine the current and expected impact of the pandemic on individuals with ADRD. We discuss and propose mitigation strategies for: the risk of COVID-19 infection and its associated morbidity and mortality for individuals with ADRD; the impact of COVID-19 on the diagnosis and clinical management of ADRD; consequences of societal responses to COVID-19 in different ADRD care settings; the effect of COVID-19 on caregivers and physicians of individuals with ADRD; mental hygiene, trauma, and stigma in the time of COVID-19; and the potential impact of COVID-19 on ADRD research. • We conclude that despite considerable uncertainty, we may be able to prevent or reduce the harm of the COVID-19 pandemic and its consequences for individuals with ADRD and their caregivers.

Children exposed to various forms of adversity early in life are at increased risk for a broad range of developmental difficulties, affecting both cognitive and emotional adjustment. We review a growing body of evidence suggesting that exposure to adverse circumstances affects the developing brain in ways that increase risk for a myriad of problems. We focus on two forms of adversity, one in which children are exposed to childhood maltreatment in family environments, and another in which children are exposed to extreme psychosocial deprivation in contexts of institutional rearing. We discuss ways in which each of these experiences represent violations of species-expected caregiving conditions, thereby imposing challenges to the developing brain. We also review emerging data pointing to the effectiveness of early intervention in remediating neurodevelopmental consequences associated with maltreatment or institutional rearing. We conclude by discussing implications of this work for public health efforts and highlight important directions for the field.

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.