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

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.

Figures

Fig. 1.

Validation of the ICA approach (Stanford University data). Axial images showing the default-mode network as detected with ROI-based (A) and ICA-based (B) approaches in a group of healthy young adults scanned on a 3-T magnet at Stanford University. The blue arrows indicate the PCC. The left side of the image corresponds to the left side of the brain. The numbers beneath each image refer to the z coordinate in Talairach space. T score bars are shown at right. Functional images were overlaid on the group-averaged structural image. Joint height and extent thresholds of P < 0.001 were used to determine significant clusters.

Fig. 2.

Hippocampal coactivation in the default-mode network (Washington University data). Axial (A) and coronal (B) images showing the default-mode network for 14 healthy young subjects scanned on a 1.5-T magnet at Washington University. The green arrows highlight the prominent bilateral coactivation in the hippocampus and underlying entorhinal cortex. The numbers beneath each coronal image refer to the y coordinate in Talairach space. Joint height and extent thresholds of P < 0.0001 were used to determine significant clusters. Other details are as in Fig. 1.

Fig. 3.

Default-mode network in healthy elderly and AD subjects (Washington University data). Axial images showing the default-mode network for the healthy elderly (A) and AD (B) groups. The blue arrows indicate the PCC. The hippocampus and underlying entorhinal cortex (green arrows) were detected bilaterally in healthy elderly subjects (A) but only in the right hemisphere in the AD group (B). Joint height and extent thresholds of P < 0.0001 were used to determine significant clusters. Other details are as in Fig. 1.

Fig. 4.

Increased default-mode network activity in healthy elderly. (A) Axial images showing the results of a two-sample t test contrasting the default-mode network in the healthy elderly group vs. the AD group. The blue arrow indicates the PCC. The magenta arrows indicate the inferior parietal lobes. (B) Coronal images showing a 112-voxel cluster in the left hippocampus (green arrows) that survived the height but not the extent threshold. Joint height and extent thresholds of P < 0.05 were used to determine significant clusters. Other details are as in Fig. 1.

Fig. 5.

Individual scores for goodness of fit to standard default-mode network. A scattergram shows the median goodness of fit for each subject in the AD and healthy elderly groups using the Stanford University ICA-derived default-mode template. The group means were significantly different in a two-sample t test (P < 0.01). The horizontal line indicates a cutoff point of 2.1 where 11 of 13 AD subjects and 10 of 13 elderly subjects are correctly categorized, yielding a sensitivity of 85% and a specificity of 77%.