OBJECTIVES: The future emergence of disease-modifying treatments for dementia highlights the urgent need to identify reliable and easily accessible tools for diagnosing Alzheimer's disease (AD). Electroencephalography (EEG) is a non-invasive and cost...
PURPOSE: Functional near-infrared spectroscopy (fNIRS) has shown feasibility in evaluating cognitive function and brain functional connectivity (FC). Therefore, this fNIRS study aimed to develop a screening method for subjective cognitive decline (SC...
INTRODUCTION: This study aimed to identify differences in the levels of inflammation-related biomarkers between patients with subcortical silent brain infarcts (SBIs) and healthy controls. We also evaluated the effect of aspirin on the subcortical SB...
BACKGROUND: Hypocretin-1 is a vital neurotransmitter in regulating the sleep-wake cycle and provides neuroprotection against cerebral ischemia. We aims to develop a poor sleep quality predictive model for elderly population with acute ischemic stroke...
BACKGROUND: As a clinical precursor to Alzheimer's disease (AD), amnestic mild cognitive impairment (aMCI) bears a considerably heightened risk of transitioning to AD compared to cognitively normal elders. Early prediction of whether aMCI will progre...
BACKGROUND: Alzheimer's disease (AD) has a major negative impact on people's quality of life, life, and health. More research is needed to determine the relationship between age and the pathologic products associated with AD. Meanwhile, the construct...
INTRODUCTION: Visual hallucination is a prevalent psychiatric disorder characterized by the occurrence of false visual perceptions due to misinterpretation in the brain. Individuals with Parkinson's disease often experience both minor and complex vis...
The prevalence of Alzheimer's disease (AD) and related dementias (ADRD) is increasing. African Americans are twice as likely to develop dementia than other ethnic populations. Traditional cognitive screening solutions lack the sensitivity to independ...
INTRODUCTION: In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We devel...