Hierarchical clustering to measure connectivity in fMRI resting-state data.

@article{citeulike:897776, abstract = {Low frequency oscillations, which are temporally correlated in functionally related brain regions, characterize the mammalian brain, even when no explicit cognitive tasks are performed. Functional connectivity MR imaging is used to map regions of the resting brain showing synchronous, regional and slow fluctuations in cerebral blood flow and oxygenation. In this study, we use a hierarchical clustering method to detect similarities of low-frequency fluctuations. We describe one measure of correlations in the low frequency range for classification of resting-state fMRI data. Furthermore, we investigate the contribution of motion and hardware instabilities to resting-state correlations and provide a method to reduce artifacts. For all cortical regions studied and clusters obtained, we quantify the degree of contamination of functional connectivity maps by the respiratory and cardiac cycle. Results indicate that patterns of functional connectivity can be obtained with hierarchical clustering that resemble known neuronal connections. The corresponding voxel time series do not show significant correlations in the respiratory or cardiac frequency band.}, address = {Department of Radiology, University of Washington, Seattle, Washington, USA. dcordes@u.washington.edu}, author = {Cordes, D. and Haughton, V. and Carew, J. D. and Arfanakis, K. and Maravilla, K. }, citeulike-article-id = {897776}, issn = {0730-725X}, journal = {Magn Reson Imaging}, keywords = {fmri, functional-connectivity, hierarchical-clustering}, month = {May}, number = {4}, pages = {305--317}, posted-at = {2007-07-16 12:04:01}, priority = {2}, title = {Hierarchical clustering to measure connectivity in fMRI resting-state data.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/12165349}, volume = {20}, year = {2002} }

TY - JOUR ID - citeulike:897776 L3 - citeulike-article-id:897776 TI - Hierarchical clustering to measure connectivity in fMRI resting-state data. JF - Magn Reson Imaging VL - 20 IS - 4 SP - 305 EP - 317 AD - Department of Radiology, University of Washington, Seattle, Washington, USA. dcordes@u.washington.edu SN - 0730-725X N2 - Low frequency oscillations, which are temporally correlated in functionally related brain regions, characterize the mammalian brain, even when no explicit cognitive tasks are performed. Functional connectivity MR imaging is used to map regions of the resting brain showing synchronous, regional and slow fluctuations in cerebral blood flow and oxygenation. In this study, we use a hierarchical clustering method to detect similarities of low-frequency fluctuations. We describe one measure of correlations in the low frequency range for classification of resting-state fMRI data. Furthermore, we investigate the contribution of motion and hardware instabilities to resting-state correlations and provide a method to reduce artifacts. For all cortical regions studied and clusters obtained, we quantify the degree of contamination of functional connectivity maps by the respiratory and cardiac cycle. Results indicate that patterns of functional connectivity can be obtained with hierarchical clustering that resemble known neuronal connections. The corresponding voxel time series do not show significant correlations in the respiratory or cardiac frequency band. KW - fmri KW - functional-connectivity KW - hierarchical-clustering AU - Cordes, D AU - Haughton, V AU - Carew, JD AU - Arfanakis, K AU - Maravilla, K PY - 2002/05// UR - http://view.ncbi.nlm.nih.gov/pubmed/12165349 ER -