The global prevalence of dementia is as high as 24 million, and has been predicted to
quadruple by the year 2050. In the US alone, Alzheimer disease (AD)–the most frequent …

The science of large-scale brain networks offers a powerful paradigm for investigating
cognitive and affective dysfunction in psychiatric and neurological disorders. This review …

Repetitive transcranial magnetic stimulation (rTMS) is emerging as a non-invasive
therapeutic strategy in the battle against Alzheimer's disease. Alzheimer's disease patients …

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. In the
last decade, studies on AD diagnosis has attached great significance to artificial intelligence …

In this article, the authors aim to maximally utilize multimodality neuroimaging and genetic
data for identifying Alzheimer's disease (AD) and its prodromal status, Mild Cognitive …

The mining of huge databases of resting-state brain activity recordings represents state of
the art in the assessment of endogenous neuronal activity—and may be a promising tool in …

Our brain is a network. It consists of spatially distributed, but functionally linked regions that
continuously share information with each other. Interestingly, recent advances in the …

Imaging has played a variety of roles in the study of Alzheimer disease (AD) over the past
four decades. Initially, computed tomography (CT) and then magnetic resonance imaging …

Dietary habits such as caloric restriction or nutrients that mimic these effects may exert
beneficial effects on brain aging. The plant-derived polyphenol resveratrol has been shown …

We performed this research to 1) evaluate a novel deep learning method for the diagnosis of
Alzheimer's disease (AD) and 2) jointly predict the Mini Mental State Examination (MMSE) …