Title
Extraction and Synchronization of BOLD Spontaneous Oscillations Using Singular Spectrum Analysis
Abstract
Spontaneous cerebral blood oxygenation level-dependent (BOLD) fluctuations are gaining interest in the neurophysiology community. These oscillations are prominent in the low-frequency range with spatiotemporal correlations. From a healthy individual, a basal resting state BOLD fMRI acquisition has been performed by collecting 4 slices. Voxel signals from seven selected regions have been considered. We assumed a composite null-hypothesis of oscillations embedded in “red noise”. To extract oscillations from BOLD signals we applied the Monte Carlo Singular Spectrum Analysis (SSA). Phase-synchronization of the oscillatory components, in the low-frequency range 0.085-0.13Hz, have been also achieved. As results, region-dependent distributions were apparent both for the noise parameters and for the number of connections between voxels. Although further studies on population samples should confirm the result consistency, the SSA technique combined with a phase-synchronization analysis seems a feasible method to extract low frequency BOLD spontaneous oscillations and to find functional connections among cerebral areas.
Year
DOI
Venue
2009
10.1109/ISDA.2009.178
ISDA
Keywords
Field
DocType
bold spontaneous,red noise,noise parameter,ssa technique,singular spectrum analysis,voxel signal,monte carlo singular spectrum,basal resting state bold,bold spontaneous oscillation,low-frequency range,cerebral area,spontaneous cerebral blood oxygenation,noise,data mining,synchronisation,phase synchronization,synchronization,resting state,monte carlo methods,low frequency,oscillations,monte carlo,neurophysiology,oscillators
Voxel,Population,Synchronization,Monte Carlo method,Colors of noise,Neurophysiology,Biological system,Pattern recognition,Computer science,Resting state fMRI,Singular spectrum analysis,Artificial intelligence
Conference
ISSN
Citations 
PageRank 
2164-7143
0
0.34
References 
Authors
1
11