Combining structural and functional neuroimaging data for studying brain connectivity: A review

被引:145
作者
Rykhlevskaia, Elena [1 ,2 ]
Gratton, Gabriele [1 ,2 ]
Fabiani, Monica [1 ,2 ]
机构
[1] Univ Illinois, Beckman Inst, Urbana, IL 61801 USA
[2] Univ Illinois, Dept Psychol, Urbana, IL 61801 USA
关键词
functional connectivity; anatomical connectivity; multimodal integration; diffusion tensor imaging (DTI); magnetic resonance imaging (MRI);
D O I
10.1111/j.1469-8986.2007.00621.x
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Different brain areas are thought to be integrated into large-scale networks to support cognitive function. Recent approaches for investigating structural organization and functional coordination within these networks involve measures of connectivity among brain areas. We review studies combining in vivo structural and functional brain connectivity data, where (a) structural connectivity analysis, mostly based on diffusion tensor imaging is paired with voxel-wise analysis of functional neuroimaging data or (b) the measurement of functional connectivity based on covariance analysis is guided/aided by structural connectivity data. These studies provide insights into the relationships between brain structure and function. Promising trends involve (a) studies where both functional and anatomical connectivity data are collected using high-resolution neuroimaging methods and (b) the development of advanced quantitative models of integration.
引用
收藏
页码:173 / 187
页数:15
相关论文
共 98 条
[1]   Exploration of the brain's white matter pathways with dynamic queries [J].
Akers, D ;
Sherbondy, A ;
Mackenzie, R ;
Dougherty, R ;
Wandell, B .
IEEE VISUALIZATION 2004, PROCEEEDINGS, 2004, :377-384
[2]  
ALLEN LS, 1991, J NEUROSCI, V11, P933
[3]  
[Anonymous], 1999, APPL MULTIVARIATE AN
[4]   Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans [J].
Ardekani, BA ;
Guckemus, S ;
Bachman, A ;
Hoptman, MJ ;
Wojtaszek, M ;
Nierenberg, J .
JOURNAL OF NEUROSCIENCE METHODS, 2005, 142 (01) :67-76
[5]   Comparison of different cortical connectivity estimators for high-resolution EEG recordings [J].
Astolfi, Laura ;
Cincotti, Febo ;
Mattia, Donatella ;
Marciani, M. Grazia ;
Baccala, Luiz A. ;
Fallani, Fabrizio de Vico ;
Salinari, Serenella ;
Ursino, Mauro ;
Zavaglia, Melissa ;
Ding, Lei ;
Edgar, J. Christopher ;
Miller, Gregory A. ;
He, Bin ;
Babiloni, Fabio .
HUMAN BRAIN MAPPING, 2007, 28 (02) :143-157
[6]   Functional connectivity: Integrating behavioral, diffusion tensor imaging, and functional magnetic resonance imaging data sets [J].
Baird, AA ;
Colvin, MK ;
VanHorn, JD ;
Inati, S ;
Gazzaniga, MS .
JOURNAL OF COGNITIVE NEUROSCIENCE, 2005, 17 (04) :687-693
[7]   A consistent relationship between local white matter architecture and functional specialisation in medial frontal cortex [J].
Behrens, TEJ ;
Jenkinson, M ;
Robson, MD ;
Smith, SM ;
Johansen-Berg, H .
NEUROIMAGE, 2006, 30 (01) :220-227
[8]   Characterization and propagation of uncertainty in diffusion-weighted MR imaging [J].
Behrens, TEJ ;
Woolrich, MW ;
Jenkinson, M ;
Johansen-Berg, H ;
Nunes, RG ;
Clare, S ;
Matthews, PM ;
Brady, JM ;
Smith, SM .
MAGNETIC RESONANCE IN MEDICINE, 2003, 50 (05) :1077-1088
[9]   Diffusion-tensor imaging-guided tracking of fibers of the pyramidal tract combined with intraoperative cortical stimulation mapping in patients with gliomas [J].
Berman, JI ;
Berger, MS ;
Mukherjee, P ;
Henry, RG .
JOURNAL OF NEUROSURGERY, 2004, 101 (01) :66-72
[10]   A Bayesian approach to modeling dynamic effective connectivity with fMRI data [J].
Bhattacharya, S ;
Ho, MHR ;
Purkayastha, S .
NEUROIMAGE, 2006, 30 (03) :794-812