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Cited by 186

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An approach for parcellating human cortical areas using resting-state correlations

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Wig, Gagan S., Laumann, Timothy O., Petersen, Steven E.·2014·NeuroImage
DOI 10.1016/j.neuroimage.2013.07.035
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Abstract

Resting State Functional Connectivity (RSFC) reveals properties related to the brain’s underlying organization and function. Features related to RSFC signals, such as the locations where the patterns of RSFC exhibit abrupt transitions, can be used to identify putative boundaries between cortical areas (RSFC-Boundary Mapping). The locations of RSFC-based area boundaries are consistent across independent groups of subjects. RSFC-based parcellation converges with parcellation information from other modalities in many locations, including task-evoked activity and probabilistic estimates of cellular architecture, providing evidence for the ability of RSFC to parcellate brain structures into functionally meaningful units. We not only highlight a collection of these observations, but also point out several limitations and observations that mandate careful consideration in using and interpreting RSFC for the purposes of parcellating the brain’s cortical and subcortical structures.

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Research works printed but not linked: 55

  1. Amunts, 2000, Brodmann's areas 17 and 18 brought into stereotaxic space—where and how variable?, NeuroImage, 11, 66, 10.1006/nimg.1999.0516 · DOI · Paper page
  2. Barnes, 2010, Identifying basal ganglia divisions in individuals using resting-state functional connectivity MRI, Front. Syst. Neurosci., 4, 18
  3. Barnes, 2012, Parcellation in left lateral parietal cortex is similar in adults and children, Cereb. Cortex, 22, 1148, 10.1093/cercor/bhr189 · DOI
  4. Birn, 2006, Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI, NeuroImage, 31, 1536, 10.1016/j.neuroimage.2006.02.048 · DOI · Paper page
  5. Biswal, 2010, Toward discovery science of human brain function, Proc. Natl. Acad. Sci. U. S. A., 107, 4734, 10.1073/pnas.0911855107 · DOI · Paper page
  6. Carmichael, 1996, Connectional networks within the orbital and medial prefrontal cortex of macaque monkeys, J. Comp. Neurol., 371, 179, 10.1002/(SICI)1096-9861(19960722)371:2<179::AID-CNE1>3.0.CO;2-# · DOI · Paper page
  7. Chang, 2010, Time–frequency dynamics of resting-state brain connectivity measured with fMRI, NeuroImage, 50, 81, 10.1016/j.neuroimage.2009.12.011 · DOI · Paper page
  8. Chang, 2009, Influence of heart rate on the BOLD signal: the cardiac response function, NeuroImage, 44, 857, 10.1016/j.neuroimage.2008.09.029 · DOI · Paper page
  9. Dale, 1993, Improved localization of cortical activity by combining EEG and MEG with cortical surface reconstruction: a linear approach, J. Cogn. Neurosci., 5, 162, 10.1162/jocn.1993.5.2.162 · DOI · Paper page
  10. Dale, 1999, Cortical surface-based analysis. I. Segmentation and surface reconstruction, NeuroImage, 9, 179, 10.1006/nimg.1998.0395 · DOI · Paper page
  11. De Martino, 2011, Whole brain high-resolution functional imaging at ultra high magnetic fields: an application to the analysis of resting state networks, NeuroImage, 57, 1031, 10.1016/j.neuroimage.2011.05.008 · DOI
  12. Dick, 2012, In vivo functional and myeloarchitectonic mapping of human primary auditory areas, J. Neurosci., 32, 16095, 10.1523/JNEUROSCI.1712-12.2012 · DOI · Paper page
  13. Doucet, 2011, Brain activity at rest: a multiscale hierarchical functional organization, J. Neurophysiol., 105, 2753, 10.1152/jn.00895.2010 · DOI · Paper page
  14. Dougherty, 2003, Visual field representations and locations of visual areas V1/2/3 in human visual cortex, J. Vis., 3, 586, 10.1167/3.10.1 · DOI · Paper page
  15. Fischl, 1999, Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system, NeuroImage, 9, 195, 10.1006/nimg.1998.0396 · DOI · Paper page
  16. Foerster, 1936, The motor cortex of man in light of Hughlings Jackson's doctrines, Brain, 58, 135, 10.1093/brain/59.2.135 · DOI · Paper page
  17. Frahm, 1988, Direct FLASH MR imaging of magnetic field inhomogeneities by gradient compensation, Magn. Reson. Med., 6, 474, 10.1002/mrm.1910060412 · DOI · Paper page
  18. Glasser, 2011, Mapping human cortical areas in vivo based on myelin content as revealed by T1- and T2-weighted MRI, J. Neurosci., 31, 11597, 10.1523/JNEUROSCI.2180-11.2011 · DOI · Paper page
  19. Goulas, 2012, Unravelling the intrinsic functional organization of the human lateral frontal cortex: a parcellation scheme based on resting state fMRI, J. Neurosci., 32, 10238, 10.1523/JNEUROSCI.5852-11.2012 · DOI
  20. Hinds, 2009, Locating the functional and anatomical boundaries of human primary visual cortex, NeuroImage, 46, 915, 10.1016/j.neuroimage.2009.03.036 · DOI
  21. Hirose, 2012, Local signal time-series during rest used for areal boundary mapping in individual human brains, PLoS One, 7, e36496, 10.1371/journal.pone.0036496 · DOI
  22. Honey, 2009, Predicting human resting-state functional connectivity from structural connectivity, Proc. Natl. Acad. Sci. U. S. A., 106, 2035, 10.1073/pnas.0811168106 · DOI · Paper page
  23. Hubel, 1962, Receptive fields, binocular interaction and functional architecture in the cat's visual cortex, J. Physiol., 160, 106, 10.1113/jphysiol.1962.sp006837 · DOI · Paper page
  24. Johansen-Berg, 2005, Functional–anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus, Cereb. Cortex, 15, 31, 10.1093/cercor/bhh105 · DOI · Paper page
  25. Kelly, 2010, Broca's region: linking human brain functional connectivity data and non-human primate tracing anatomy studies, Eur. J. Neurosci., 32, 383, 10.1111/j.1460-9568.2010.07279.x · DOI · Paper page
  26. Kim, 2010, Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method, NeuroImage, 49, 2375, 10.1016/j.neuroimage.2009.10.016 · DOI · Paper page
  27. Kim, 2013, Functional connectivity-based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI, Hum. Brain Mapp., 34, 1371, 10.1002/hbm.21517 · DOI
  28. Lancaster, 1995, A modality-independent approach to spatial normalization of tomographic images of the human brain, Hum. Brain Mapp., 3, 209, 10.1002/hbm.460030305 · DOI · Paper page
  29. Mars, 2012, Connectivity-based subdivisions of the human right “temporoparietal junction area”: evidence for different areas participating in different cortical networks, Cereb. Cortex, 22, 1894, 10.1093/cercor/bhr268 · DOI · Paper page
  30. Miezin, 2000, Characterizing the hemodynamic response: effects of presentation rate, sampling procedure, and the possibility of ordering brain activity based on relative timing, NeuroImage, 11, 735, 10.1006/nimg.2000.0568 · DOI · Paper page
  31. Mugler, 1990, Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE), Magn. Reson. Med., 15, 152, 10.1002/mrm.1910150117 · DOI · Paper page
  32. Mumford, 2010, Detecting network modules in fMRI time series: a weighted network analysis approach, NeuroImage, 52, 1465, 10.1016/j.neuroimage.2010.05.047 · DOI
  33. Nelson, 2010, A parcellation scheme for human left lateral parietal cortex, Neuron, 67, 156, 10.1016/j.neuron.2010.05.025 · DOI · Paper page
  34. Ojemann, 1997, Anatomic localization and quantitative analysis of gradient refocused echo-planar fMRI susceptibility artifacts, NeuroImage, 6, 156, 10.1006/nimg.1997.0289 · DOI · Paper page
  35. Petersen, 1988, Positron emission tomographic studies of the cortical anatomy of single-word processing, Nature, 331, 585, 10.1038/331585a0 · DOI · Paper page
  36. Power, 2012, Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion, NeuroImage, 59, 2142, 10.1016/j.neuroimage.2011.10.018 · DOI · Paper page
  37. Ryali, 2013, A parcellation scheme based on von Mises–Fisher distributions and Markov random fields for segmenting brain regions using resting-state fMRI, NeuroImage, 65, 83, 10.1016/j.neuroimage.2012.09.067 · DOI
  38. Sabuncu, 2010, Function-based intersubject alignment of human cortical anatomy, Cereb. Cortex, 20, 130, 10.1093/cercor/bhp085 · DOI · Paper page
  39. Satterthwaite, 2012, Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth, NeuroImage, 60, 623, 10.1016/j.neuroimage.2011.12.063 · DOI · Paper page
  40. Schleicher, 1990, A quantitative approach to cytoarchitectonics: analysis of structural inhomogeneities in nervous tissue using an image analyser, J. Microsc., 157, 367, 10.1111/j.1365-2818.1990.tb02971.x · DOI
  41. Schormann, 1998, Three-dimensional linear and nonlinear transformations: an integration of light microscopical and MRI data, Hum. Brain Mapp., 6, 339, 10.1002/(SICI)1097-0193(1998)6:5/6<339::AID-HBM3>3.0.CO;2-Q · doi:10.1002/(sici)1097-0193(1998)6:5/6<339::aid-hbm3>3.0.co;2-q
  42. Ségonne, 2004, A hybrid approach to the skull stripping problem in MRI, NeuroImage, 22, 1060, 10.1016/j.neuroimage.2004.03.032 · DOI · Paper page
  43. Ségonne, 2005, A genetic algorithm for the topology correction of cortical surfaces, Inf. Process. Med. Imaging, 19, 393, 10.1007/11505730_33 · DOI
  44. Sereno, 1995, Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging, Science, 268, 889, 10.1126/science.7754376 · DOI · Paper page
  45. Toga, 2006, Towards multimodal atlases of the human brain, Nat. Rev. Neurosci., 7, 952, 10.1038/nrn2012 · DOI · Paper page
  46. Uddin, 2010, Dissociable connectivity within human angular gyrus and intraparietal sulcus: evidence from functional and structural connectivity, Cereb. Cortex, 20, 2636, 10.1093/cercor/bhq011 · DOI · Paper page
  47. Van Dijk, 2012, The influence of head motion on intrinsic functional connectivity MRI, NeuroImage, 59, 431, 10.1016/j.neuroimage.2011.07.044 · DOI · Paper page
  48. Van Essen, 2005, A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex, NeuroImage, 28, 635, 10.1016/j.neuroimage.2005.06.058 · DOI · Paper page
  49. Van Essen, 1981, The middle temporal visual area in the macaque: myeloarchitecture, connections, functional properties and topographic organization, J. Comp. Neurol., 199, 293, 10.1002/cne.901990302 · DOI · Paper page
  50. Van Essen, 2001, An integrated software suite for surface-based analyses of cerebral cortex, J. Am. Med. Inform. Assoc., 8, 443, 10.1136/jamia.2001.0080443 · DOI · Paper page
  51. Van Essen, 2012, The Human Connectome Project: a data acquisition perspective, NeuroImage, 62, 2222, 10.1016/j.neuroimage.2012.02.018 · DOI · Paper page
  52. Vogt, 1919, Allgemeine Ergebnisse unserer Hirnforschung, J. Psychol. Neurol., 25, 273
  53. Wig, 2011, Concepts and principles in the analysis of brain networks, Ann. N. Y. Acad. Sci., 1224, 126, 10.1111/j.1749-6632.2010.05947.x · DOI · Paper page
  54. Wig, 2013, Parcellating an individual subject's cortical and subcortical brain structures using snowball sampling of resting-state correlations, Cereb. Cortex
  55. Zhang, 2008, Intrinsic functional relations between human cerebral cortex and thalamus, J. Neurophysiol., 100, 1740, 10.1152/jn.90463.2008 · DOI · Paper page

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Metadata

Authors
Wig, G. S., Laumann, T. O., & Petersen, S. E.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2014-06
Volume
93
Pages
276-291
ISSN
1053-8119 (ISSN-L)
DOI
10.1016/j.neuroimage.2013.07.035
OpenAlex
W2073391538
Cited by
186
References
26
FWCI
10.27
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Funders
  • McDonnell Foundation Collaborative Action Award
  • NIH (32979, 46424, 61144)
  • Human Connectome Project (1U54MH091657)
  • NIH Blueprint for Neuroscience Research

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Wig, G. S., Laumann, T. O., & Petersen, S. E. (2014). An approach for parcellating human cortical areas using resting-state correlations. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.07.035

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