A Symmetry-Based Method to Infer Structural Brain Networks from Probabilistic Tractography Data
Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP) have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that in...
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| Published in: | Frontiers in neuroinformatics Vol. 10; p. 46 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Frontiers Research Foundation
04.11.2016
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| ISSN: | 1662-5196, 1662-5196 |
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| Abstract | Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP) have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction. |
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| AbstractList | Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP) have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction.Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP) have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction. Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP)1 have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction. Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP) have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction. |
| Author | Shadi, Kamal Bakhshi, Saideh Mayberg, Helen S. Dovrolis, Constantine Gutman, David A. |
| AuthorAffiliation | 1 School of Computer Science, Georgia Institute of Technology Atlanta, GA, USA 3 Psychiatric Neuroimaging and Therapeutics, Department of Psychiatry, Neurology, and Radiology, Emory University Atlanta, GA, USA 2 Department of Neurology, Psychiatry and Biomedical Informatics, Emory University Atlanta, GA, USA |
| AuthorAffiliation_xml | – name: 2 Department of Neurology, Psychiatry and Biomedical Informatics, Emory University Atlanta, GA, USA – name: 1 School of Computer Science, Georgia Institute of Technology Atlanta, GA, USA – name: 3 Psychiatric Neuroimaging and Therapeutics, Department of Psychiatry, Neurology, and Radiology, Emory University Atlanta, GA, USA |
| Author_xml | – sequence: 1 givenname: Kamal surname: Shadi fullname: Shadi, Kamal – sequence: 2 givenname: Saideh surname: Bakhshi fullname: Bakhshi, Saideh – sequence: 3 givenname: David A. surname: Gutman fullname: Gutman, David A. – sequence: 4 givenname: Helen S. surname: Mayberg fullname: Mayberg, Helen S. – sequence: 5 givenname: Constantine surname: Dovrolis fullname: Dovrolis, Constantine |
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| CitedBy_id | crossref_primary_10_1016_j_neuroimage_2017_12_064 crossref_primary_10_3389_fneur_2018_00439 crossref_primary_10_1016_j_neuroimage_2022_119553 crossref_primary_10_3389_fnsys_2020_00042 |
| Cites_doi | 10.1016/j.neurobiolaging.2013.03.028 10.1093/cercor/bhu326 10.1016/j.neuroimage.2013.03.053 10.1016/j.neuroimage.2012.06.002 10.1016/j.neuroimage.2013.03.024 10.1016/j.neuroimage.2012.06.081 10.1016/j.neuroimage.2009.12.027 10.1523/JNEUROSCI.0493-16.2016 10.1016/j.neuroimage.2009.10.003 10.1192/bjp.bp.113.137380 10.1371/journal.pcbi.1000395 10.1523/JNEUROSCI.1929-08.2008 10.1089/brain.2012.0137 10.1109/TMI.2008.2004424 10.1152/jn.00338.2011 10.1371/journal.pone.0013701 10.1016/j.jneumeth.2011.09.021 10.1016/j.neuroimage.2010.01.019 10.1177/070674371405900602 10.1073/pnas.0811168106 10.1016/j.neuroimage.2016.09.053. 10.1016/j.neuroimage.2006.09.018 10.1016/j.neuroimage.2012.03.071 10.1016/j.pneurobio.2013.06.003 10.1038/nn.4361 10.1002/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3 10.1523/JNEUROSCI.2419-07.2007 10.7551/mitpress/9266.001.0001 10.1016/j.neuroimage.2010.09.006 10.1073/pnas.1405672111 10.3389/fninf.2014.00046 10.1016/j.neuroimage.2011.01.032 10.1089/brain.2011.0011 10.1016/j.neuroimage.2008.12.049 10.1016/S1474-4422(08)70163-7 10.1007/s00429-009-0208-6 10.1038/nn.4134 10.1016/j.neuron.2005.02.014 10.1002/hbm.21333 10.1093/acprof:oso/9780199206650.001.0001 10.1371/journal.pcbi.0010042 10.1016/j.neuroimage.2012.12.066 10.1016/j.neuroimage.2008.08.010 10.1038/nmeth.2485 10.1523/JNEUROSCI.2177-05.2005 10.1038/nature18933 10.1016/j.neuroimage.2016.06.035. 10.1016/j.euroneuro.2014.02.011 10.1145/1411509.1411513 10.1093/cercor/bhn059 10.1002/1097-0193(200007)10:3120::AID-HBM303.0.CO;2-8 10.3389/fnins.2014.00167 10.1006/nimg.2001.0978 10.1002/mrm.21789 10.1002/mrm.22159 10.1002/(SICI)1097-0193(1997)5:4<228::AID-HBM4>3.0.CO;2-5 10.1002/mrm.25045 10.1089/brain.2011.0033 10.1016/S1361-8415(01)00036-6 10.1371/journal.pone.0000597 10.1016/j.neuroimage.2013.05.041 10.1176/jnp.9.3.471 10.1016/j.biopsych.2008.07.026 10.1093/cercor/bhn102 10.1098/rstb.2005.1631 10.1016/j.neuroimage.2004.01.015 10.1002/jmri.10350 10.1002/hbm.22828 10.1002/hbm.21332 10.1002/mrm.10609 10.1371/journal.pbio.0060159 10.1016/j.neuroimage.2008.06.012 10.1073/pnas.1418198112 10.1016/j.neuron.2011.09.006 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Present Address: Saideh Bakhshi, HCI Research Group, Yahoo Labs, San Francisco, CA, USA Reviewed by: Jeffrey Thomas Duda, University of Pennsylvania, USA; Arnaud Messé, Universitätsklinikum Hamburg-Eppendorf, Germany Edited by: Arjen Van Ooyen, VU University Amsterdam, Netherlands |
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| References | Zalesky (B77) 2010; 50 Sporns (B64) 2013; 10 Zalesky (B76) 2016 Duda (B22) 2014; 8 Fillard (B24) 2011; 56 Daianu (B16) 2013; 3 de Reus (B19) 2013b; 80 Mayberg (B43) 2005; 45 Cheng (B12) 2012; 203 Peterson (B51) 2014; 59 Damoiseaux (B17) 2009; 213 Tzourio-Mazoyer (B70) 2002; 15 Jenkinson (B36) 2001; 5 Bassett (B3) 2011; 54 Yeo (B75) 2011; 106 Elman (B23) 2013; 109 Donahue (B21) 2016; 36 Schalekamp (B61) 2009 Ailon (B1) 2008; 55 Behrens (B6) 2007; 34 Glasser (B26) 2016a; 536 Poupon (B54) 2010 Chen (B11) 2013; 34 Azadbakht (B2) 2015; 25 Craddock (B15) 2012; 33 Van Essen (B73) 2013; 80 McIntosh (B44) 2008; 64 Blumensath (B9) 2013; 76 Thirion (B67) 2014; 8 Neher (B48) 2014; 72 van den Heuvel (B72) 2008; 43 Honey (B32) 2009; 106 Jbabdi (B35) 2015; 18 James (B33) 2009; 45 Petrides (B52) 2005; 360 Bastiani (B5) 2012; 62 Jones (B37) 2013; 73 Parker (B50) 2003; 18 Descoteaux (B20) 2009; 28 Ciccarelli (B13) 2008; 7 Fornito (B25) 2015; 25 Seminowicz (B62) 2004; 22 Bassett (B4) 2008; 28 Gong (B28) 2009; 19 de Reus (B18) 2013a; 70 Rubinov (B60) 2010; 52 Mori (B46) 1999; 45 Thomas (B68) 2014; 111 Li (B40) 2012b; 33 van den Heuvel (B71) 2015; 36 Roberts (B58) 2016 Glasser (B27) 2016b; 19 Buckner (B10) 2005; 25 Petrides (B53) 2007; 27 Newman (B49) 2010 Taljan (B66) 2011; 1 Beucke (B8) 2014; 205 Lancaster (B38) 2000; 10 Morris (B47) 2008; 42 Craddock (B14) 2009; 62 Power (B56) 2011; 72 Robinson (B59) 2010; 50 Sporns (B63) 2012 Sporns (B65) 2005; 1 Hagmann (B31) 2007; 2 Li (B41) 2009; 5 McKeown (B45) 1997 Van Wijk (B74) 2010; 5 Mayberg (B42) 1997; 9 Behrens (B7) 2003; 50 Poupon (B55) 2008; 60 Li (B39) 2012a; 61 Greicius (B29) 2009; 19 Reveley (B57) 2015; 112 Jbabdi (B34) 2011; 1 Tzourio (B69) 1997; 5 Hagmann (B30) 2008; 6 |
| References_xml | – volume: 34 start-page: 2248 year: 2013 ident: B11 article-title: Brain aging in humans, chimpanzees (Pan troglodytes), and rhesus macaques (Macaca mulatta): magnetic resonance imaging studies of macro-and microstructural changes publication-title: Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2013.03.028 – volume: 25 start-page: 4299 year: 2015 ident: B2 article-title: Validation of high-resolution tractography against in vivo tracing in the macaque visual cortex publication-title: Cereb. Cortex doi: 10.1093/cercor/bhu326 – volume: 80 start-page: 397 year: 2013b ident: B19 article-title: The parcellation-based connectome: limitations and extensions publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.03.053 – volume: 62 start-page: 1732 year: 2012 ident: B5 article-title: Human cortical connectome reconstruction from diffusion weighted MRI: the effect of tractography algorithm publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.06.002 – volume: 76 start-page: 313 year: 2013 ident: B9 article-title: Spatially constrained hierarchical parcellation of the brain with resting-state fMRI publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.03.024 – volume: 73 start-page: 239 year: 2013 ident: B37 article-title: White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.06.081 – volume: 50 start-page: 970 year: 2010 ident: B77 article-title: Whole-brain anatomical networks: does the choice of nodes matter? publication-title: Neuroimage doi: 10.1016/j.neuroimage.2009.12.027 – volume: 36 start-page: 6758 year: 2016 ident: B21 article-title: Using diffusion tractography to predict cortical connection strength and distance: a quantitative comparison with tracers in the monkey publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.0493-16.2016 – volume: 52 start-page: 1059 year: 2010 ident: B60 article-title: Complex network measures of brain connectivity: uses and interpretations publication-title: Neuroimage doi: 10.1016/j.neuroimage.2009.10.003 – volume: 205 start-page: 376 year: 2014 ident: B8 article-title: Default mode network subsystem alterations in obsessive-compulsive disorder publication-title: Br. J. Psychiatry doi: 10.1192/bjp.bp.113.137380 – volume: 5 start-page: e1000395 year: 2009 ident: B41 article-title: Brain anatomical network and intelligence publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1000395 – volume: 28 start-page: 9239 year: 2008 ident: B4 article-title: Hierarchical organization of human cortical networks in health and schizophrenia publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.1929-08.2008 – volume: 3 start-page: 407 year: 2013 ident: B16 article-title: Breakdown of brain connectivity between normal aging and Alzheimer's disease: a structural k-core network analysis publication-title: Brain Connect. doi: 10.1089/brain.2012.0137 – volume: 28 start-page: 269 year: 2009 ident: B20 article-title: Deterministic and probabilistic tractography based on complex fibre orientation distributions publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2008.2004424 – volume: 106 start-page: 1125 year: 2011 ident: B75 article-title: The organization of the human cerebral cortex estimated by intrinsic functional connectivity publication-title: J. Neurophysiol. doi: 10.1152/jn.00338.2011 – volume: 5 start-page: e13701 year: 2010 ident: B74 article-title: Comparing brain networks of different size and connectivity density using graph theory publication-title: PLoS ONE doi: 10.1371/journal.pone.0013701 – volume: 203 start-page: 264 year: 2012 ident: B12 article-title: Optimization of seed density in DTI tractography for structural networks publication-title: J. Neurosci. Methods doi: 10.1016/j.jneumeth.2011.09.021 – volume: 50 start-page: 910 year: 2010 ident: B59 article-title: Identifying population differences in whole-brain structural networks: a machine learning approach publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.01.019 – volume: 59 start-page: 294 year: 2014 ident: B51 article-title: Resting-state neuroimaging studies: a new way of identifying differences and similarities among the anxiety disorders? publication-title: Can. J. Psychiatry doi: 10.1177/070674371405900602 – volume: 106 start-page: 2035 year: 2009 ident: B32 article-title: Predicting human resting-state functional connectivity from structural connectivity publication-title: Proc. Natl. Acad. Sci. U.S.A. doi: 10.1073/pnas.0811168106 – year: 2016 ident: B58 article-title: Consistency-based thresholding of the human connectome publication-title: Neuroimage doi: 10.1016/j.neuroimage.2016.09.053. – volume: 34 start-page: 144 year: 2007 ident: B6 article-title: Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? publication-title: Neuroimage doi: 10.1016/j.neuroimage.2006.09.018 – volume: 61 start-page: 1017 year: 2012a ident: B39 article-title: Quantitative assessment of a framework for creating anatomical brain networks via global tractography publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.03.071 – volume: 109 start-page: 1 year: 2013 ident: B23 article-title: Pain and suicidality: insights from reward and addiction neuroscience publication-title: Prog. Neurobiol. doi: 10.1016/j.pneurobio.2013.06.003 – volume-title: Proceedings of the International Society for Magnetic Resonance in Medicine year: 2010 ident: B54 article-title: A diffusion hardware phantom looking like a coronal brain slice – volume: 19 start-page: 1175 year: 2016b ident: B27 article-title: The Human Connectome Project's neuroimaging approach publication-title: Nat. Neurosci. doi: 10.1038/nn.4361 – volume: 45 start-page: 265 year: 1999 ident: B46 article-title: Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging publication-title: Ann. Neurol. doi: 10.1002/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3 – volume: 27 start-page: 11573 year: 2007 ident: B53 article-title: Efferent association pathways from the rostral prefrontal cortex in the macaque monkey publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.2419-07.2007 – volume-title: Discovering the Human Connectome year: 2012 ident: B63 doi: 10.7551/mitpress/9266.001.0001 – volume: 54 start-page: 1262 year: 2011 ident: B3 article-title: Conserved and variable architecture of human white matter connectivity publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.09.006 – volume: 111 start-page: 16574 year: 2014 ident: B68 article-title: Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited publication-title: Proc. Natl. Acad. Sci. U.S.A. doi: 10.1073/pnas.1405672111 – volume: 8 start-page: 46 year: 2014 ident: B22 article-title: Reproducibility of graph metrics of human brain structural networks publication-title: Front. Neuroinform. doi: 10.3389/fninf.2014.00046 – volume: 56 start-page: 220 year: 2011 ident: B24 article-title: Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom publication-title: Neuroimage doi: 10.1016/j.neuroimage.2011.01.032 – volume: 1 start-page: 111 year: 2011 ident: B66 article-title: Anatomical connectivity between subcortical structures publication-title: Brain Connect. doi: 10.1089/brain.2011.0011 – volume: 45 start-page: 778 year: 2009 ident: B33 article-title: Exploratory structural equation modeling of resting-state fMRI: applicability of group models to individual subjects publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.12.049 – volume: 7 start-page: 715 year: 2008 ident: B13 article-title: Diffusion-based tractography in neurological disorders: concepts, applications, and future developments publication-title: Lancet Neurol. doi: 10.1016/S1474-4422(08)70163-7 – volume-title: Analysis of fMRI Data by Blind Separation into Independent Spatial Components. year: 1997 ident: B45 – volume: 213 start-page: 525 year: 2009 ident: B17 article-title: Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity publication-title: Brain Struct. Funct. doi: 10.1007/s00429-009-0208-6 – start-page: 38 volume-title: ALENEX year: 2009 ident: B61 article-title: Rank aggregation: together we're strong – volume: 18 start-page: 1546 year: 2015 ident: B35 article-title: Measuring macroscopic brain connections in vivo publication-title: Nat. Neurosci. doi: 10.1038/nn.4134 – volume: 45 start-page: 651 year: 2005 ident: B43 article-title: Deep brain stimulation for treatment-resistant depression publication-title: Neuron doi: 10.1016/j.neuron.2005.02.014 – volume: 33 start-page: 1914 year: 2012 ident: B15 article-title: A whole brain fMRI atlas generated via spatially constrained spectral clustering publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.21333 – volume-title: Networks: An Introduction year: 2010 ident: B49 doi: 10.1093/acprof:oso/9780199206650.001.0001 – volume: 1 start-page: e42 year: 2005 ident: B65 article-title: The human connectome: a structural description of the human brain publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.0010042 – volume: 70 start-page: 402 year: 2013a ident: B18 article-title: Estimating false positives and negatives in brain networks publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.12.066 – volume: 43 start-page: 528 year: 2008 ident: B72 article-title: Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.08.010 – volume: 10 start-page: 491 year: 2013 ident: B64 article-title: Making sense of brain network data publication-title: Nat. Methods doi: 10.1038/nmeth.2485 – volume: 25 start-page: 7709 year: 2005 ident: B10 article-title: Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.2177-05.2005 – volume: 536 start-page: 171 year: 2016a ident: B26 article-title: A multi-modal parcellation of human cerebral cortex publication-title: Nature doi: 10.1038/nature18933 – year: 2016 ident: B76 article-title: Connectome sensitivity or specificity: which is more important? publication-title: Neuroimage doi: 10.1016/j.neuroimage.2016.06.035. – volume: 25 start-page: 733 year: 2015 ident: B25 article-title: Connectomics: a new paradigm for understanding brain disease publication-title: Eur. Neuropsychopharmacol. doi: 10.1016/j.euroneuro.2014.02.011 – volume: 55 start-page: 23 year: 2008 ident: B1 article-title: Aggregating inconsistent information: ranking and clustering publication-title: J. ACM doi: 10.1145/1411509.1411513 – volume: 19 start-page: 72 year: 2009 ident: B29 article-title: Resting-state functional connectivity reflects structural connectivity in the default mode network publication-title: Cereb. Cortex doi: 10.1093/cercor/bhn059 – volume: 10 start-page: 120 year: 2000 ident: B38 article-title: Automated Talairach atlas labels for functional brain mapping publication-title: Hum. Brain Mapp. doi: 10.1002/1097-0193(200007)10:3120::AID-HBM303.0.CO;2-8 – volume: 8 start-page: 167 year: 2014 ident: B67 article-title: Which fMRI clustering gives good brain parcellations? publication-title: Front. Neurosci. doi: 10.3389/fnins.2014.00167 – volume: 15 start-page: 273 year: 2002 ident: B70 article-title: Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain publication-title: Neuroimage doi: 10.1006/nimg.2001.0978 – volume: 60 start-page: 1276 year: 2008 ident: B55 article-title: New diffusion phantoms dedicated to the study and validation of high-angular-resolution diffusion imaging (HARDI) models publication-title: Magn. Reson. Med. doi: 10.1002/mrm.21789 – volume: 62 start-page: 1619 year: 2009 ident: B14 article-title: Disease state prediction from resting state functional connectivity publication-title: Magn. Reson. Med. doi: 10.1002/mrm.22159 – volume: 5 start-page: 228 year: 1997 ident: B69 article-title: Use of anatomical parcellation to catalog and study structure-function relationships in the human brain publication-title: Hum. Brain Mapp. doi: 10.1002/(SICI)1097-0193(1997)5:4<228::AID-HBM4>3.0.CO;2-5 – volume: 72 start-page: 1460 year: 2014 ident: B48 article-title: Fiberfox: facilitating the creation of realistic white matter software phantoms publication-title: Magn. Reson. Med. doi: 10.1002/mrm.25045 – volume: 1 start-page: 169 year: 2011 ident: B34 article-title: Tractography: where do we go from here? publication-title: Brain Connect. doi: 10.1089/brain.2011.0033 – volume: 5 start-page: 143 year: 2001 ident: B36 article-title: A global optimisation method for robust affine registration of brain images publication-title: Med. Image Anal. doi: 10.1016/S1361-8415(01)00036-6 – volume: 2 start-page: e597 year: 2007 ident: B31 article-title: Mapping human whole-brain structural networks with diffusion MRI publication-title: PLoS ONE doi: 10.1371/journal.pone.0000597 – volume: 80 start-page: 62 year: 2013 ident: B73 article-title: The WU-Minn human connectome project: an overview publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.05.041 – volume: 9 start-page: 471 year: 1997 ident: B42 article-title: Limbic-cortical dysregulation: a proposed model of depression publication-title: J. Neuropsychiatry Clin. Neurosci. doi: 10.1176/jnp.9.3.471 – volume: 64 start-page: 1088 year: 2008 ident: B44 article-title: White matter tractography in bipolar disorder and schizophrenia publication-title: Biol. Psychiatry doi: 10.1016/j.biopsych.2008.07.026 – volume: 19 start-page: 524 year: 2009 ident: B28 article-title: Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography publication-title: Cereb. Cortex doi: 10.1093/cercor/bhn102 – volume: 360 start-page: 781 year: 2005 ident: B52 article-title: Lateral prefrontal cortex: architectonic and functional organization publication-title: Philos. Trans. R. Soc. B Biol. Sci. doi: 10.1098/rstb.2005.1631 – volume: 22 start-page: 409 year: 2004 ident: B62 article-title: Limbic-frontal circuitry in major depression: a path modeling metanalysis publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.01.015 – volume: 18 start-page: 242 year: 2003 ident: B50 article-title: A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements publication-title: J. Magn. Reson. Imaging doi: 10.1002/jmri.10350 – volume: 36 start-page: 3064 year: 2015 ident: B71 article-title: Comparison of diffusion tractography and tract-tracing measures of connectivity strength in rhesus macaque connectome publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.22828 – volume: 33 start-page: 1894 year: 2012b ident: B40 article-title: The effects of connection reconstruction method on the interregional connectivity of brain networks via diffusion tractography publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.21332 – volume: 50 start-page: 1077 year: 2003 ident: B7 article-title: Characterization and propagation of uncertainty in diffusion-weighted MR imaging publication-title: Magn. Reson. Med. doi: 10.1002/mrm.10609 – volume: 6 start-page: e159 year: 2008 ident: B30 article-title: Mapping the structural core of human cerebral cortex publication-title: PLoS Biol. doi: 10.1371/journal.pbio.0060159 – volume: 42 start-page: 1329 year: 2008 ident: B47 article-title: Probabilistic fibre tracking: differentiation of connections from chance events publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.06.012 – volume: 112 start-page: E2820 year: 2015 ident: B57 article-title: Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography publication-title: Proc. Natl. Acad. Sci. U.S.A. doi: 10.1073/pnas.1418198112 – volume: 72 start-page: 665 year: 2011 ident: B56 article-title: Functional network organization of the human brain publication-title: Neuron doi: 10.1016/j.neuron.2011.09.006 |
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