Brain atrophy measured by MRI, cerebral glucose metabolism measured by the uptake of 18F labeled fluorodeoxyglucose (FDG) using positron emission tomography (PET), and neuronal activity inferred from blood oxygen level dependent (BOLD) contrast in functional MRI represent established biomarkers associated with disease progression and treatment response in Alzheimer disease (AD). In this study we utilized a new metric for neuronal activity based on the standard deviation of the magnitude of the resting-state BOLD signal fluctuation. The purpose of this study was to determine whether this new metric could be used to accurately differentiate healthy individuals from people with Alzheimer disease. Data were obtained from the Alzheimer disease neuroimaging initiative (ADNI) database for 15 normal elderly controls (NEC) and 15 aged-matched AD subjects. The brain extracted RS-fMRI data were preprocessed, and co-registered to standard Montreal neurological institute (MNI)-152 space. An independent component analysis method was applied to each dataset followed by a multiple-template matching technique and neuronality test to identify neuronal components using a support vector machine classifier. A brain activity map was constructed based on the BOLD signal variation of these neuronal components. Our results revealed that the mean brain activity measured by RS-fMRI was significantly lower (p< 0.05) in several brain regions including the hippocampus in AD compared to NEC. A classification model based on neuronal activity in the hippocampus measured by RS-fMRI achieved 75% average classification accuracy, 70% sensitivity, and 78% specificity. The RS-fMRI brain activity biomarker was also positively correlated with cognitive scores and amyloid beta1-42 CSF levels (p < 0.05). Unpaired t-test showed significantly fewer neuronal components in the AD group compared to the NEC group (p<0.01), consistent with previous RS-fMRI studies that showed decreased functional connectivity in AD group. The RS-fMRI derived brain activity measurement could differentiate patients with AD and NEC. This measurement could help in the early detection of AD and monitoring of disease progression.