Paper
30 April 2004 Online detection of low-frequency functional connectivity
Author Affiliations +
Abstract
Synchronized oscillations in resting state timecourses have been detected in recent fMRI studies. These oscillations are low frequency in nature (<0.08 Hz), and seem to be a property of symmetric cortices. These fluctuations are important as a pontential signal of interest, which could indicate connectivity between functionally related areas of the brain. It has also been shown that the synchronized oscillations decrease in some spontaneous pathological states (such as cocaine injection). Thus, detection of these functional connectivity patterns may help to serve as a guage of normal brain activity. Currently, functional connectivity detection is applied only in offline post-processing analysis. Online detection methods have been applied to detect task activation in functional MRI. This allows real-time analysis of fMRI results, and could be important in detecting short-term changes in functional states. In this work, we develop an outline algorithm to detect low frequency resting state functional connectivity in real time. This will extend connectivity analysis to allow online detection of changes in "resting state" brain networks.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Scott J. Peltier, Stephen M. LaConte, and Xiaoping Hu "Online detection of low-frequency functional connectivity", Proc. SPIE 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, (30 April 2004); https://doi.org/10.1117/12.535764
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Cited by 1 scholarly publication.
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KEYWORDS
Linear filtering

Magnetic resonance imaging

Brain

Statistical analysis

Data acquisition

Algorithm development

Functional magnetic resonance imaging

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