Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI

Proc Natl Acad Sci U S A. 2004 Mar 30;101(13):4637-42. doi: 10.1073/pnas.0308627101. Epub 2004 Mar 15.

Abstract

Recent functional imaging studies have revealed coactivation in a distributed network of cortical regions that characterizes the resting state, or default mode, of the human brain. Among the brain regions implicated in this network, several, including the posterior cingulate cortex and inferior parietal lobes, have also shown decreased metabolism early in the course of Alzheimer's disease (AD). We reasoned that default-mode network activity might therefore be abnormal in AD. To test this hypothesis, we used independent component analysis to isolate the network in a group of 13 subjects with mild AD and in a group of 13 age-matched elderly controls as they performed a simple sensory-motor processing task. Three important findings are reported. Prominent coactivation of the hippocampus, detected in all groups, suggests that the default-mode network is closely involved with episodic memory processing. The AD group showed decreased resting-state activity in the posterior cingulate and hippocampus, suggesting that disrupted connectivity between these two regions accounts for the posterior cingulate hypometabolism commonly detected in positron emission tomography studies of early AD. Finally, a goodness-of-fit analysis applied at the individual subject level suggests that activity in the default-mode network may ultimately prove a sensitive and specific biomarker for incipient AD.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aging / physiology*
  • Alzheimer Disease / physiopathology*
  • Brain / anatomy & histology
  • Brain / pathology*
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Nerve Net / pathology
  • Nerve Net / physiology*
  • Reaction Time
  • Reference Values
  • Reproducibility of Results