Details

Autor(en) / Beteiligte

• Jones, David T
• Vemuri, Prashanthi
• Murphy, Matthew C
• Gunter, Jeffrey L
• Senjem, Matthew L
• Machulda, Mary M
• Przybelski, Scott A
• Gregg, Brian E
• Kantarci, Kejal
• Knopman, David S
• Boeve, Bradley F
• Petersen, Ronald C
• Jack, Jr, Clifford R
• He, Yong

Titel

Non-stationarity in the "resting brain's" modular architecture

Ist Teil von

• PloS one, 2012-06, Vol.7 (6), p.e39731-e39731

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2012

Link zum Volltext

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain's modular organization and assign each region to a "meta-modular" group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer's dementia and 56 cognitively normal elderly subjects matched 1:2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer's disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer's dementia.