Brain Anatomical Network and Intelligence
Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in i...
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| Published in | PLoS computational biology Vol. 5; no. 5; p. e1000395 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
01.05.2009
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. |
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| AbstractList | Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.
Networks of interconnected brain regions coordinate brain activities. Information is processed in the grey matter (cortex and subcortical structures) and passed along the network via whitish, fatty-coated fiber bundles, the white matter. Using maps of these white matter tracks, we provided evidence that higher intelligence may result from more efficient information transfer. Specifically, we hypothesized that higher IQ derives from higher global efficiency of the brain anatomical network. Seventy-nine healthy young adults were divided into general and high IQ groups. We used diffusion tensor tractography, which maps brain white matter fibers, to construct anatomical brain networks for each subject and calculated the network properties using both binary and weighted networks. We consistently found that the high intelligence group's brain network was significantly more efficient than was the general intelligence group's. Moreover, IQ scores were significantly correlated with network properties, such as shorter path lengths and higher overall efficiency, indicating that the information transfer in the brain was more efficient. These converging evidences support the hypothesis that the efficiency of the organization of the brain structure may be an important biological basis for intelligence. Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. |
| Audience | Academic |
| Author | Li, Jun Yu, Chunshui Jiang, Tianzi Li, Kuncheng Qin, Wen Li, Yonghui Liu, Yong |
| AuthorAffiliation | 1 LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China Indiana University, United States of America 2 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China 3 Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China |
| AuthorAffiliation_xml | – name: 1 LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China – name: Indiana University, United States of America – name: 3 Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China – name: 2 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China |
| Author_xml | – sequence: 1 givenname: Yonghui surname: Li fullname: Li, Yonghui – sequence: 2 givenname: Yong surname: Liu fullname: Liu, Yong – sequence: 3 givenname: Jun surname: Li fullname: Li, Jun – sequence: 4 givenname: Wen surname: Qin fullname: Qin, Wen – sequence: 5 givenname: Kuncheng surname: Li fullname: Li, Kuncheng – sequence: 6 givenname: Chunshui surname: Yu fullname: Yu, Chunshui – sequence: 7 givenname: Tianzi surname: Jiang fullname: Jiang, Tianzi |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19492086$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1162/jocn.2006.18.3.320 10.1093/brain/119.5.1763 10.1016/j.cub.2004.05.008 10.1016/S0140-6736(02)08615-4 10.1016/j.neulet.2003.10.063 10.1385/NI:2:3:353 10.1002/1097-4679(199205)48:3<360::AID-JCLP2270480314>3.0.CO;2-P 10.1017/S0140525X07001185 10.1038/30918 10.1148/radiol.2301021640 10.1016/j.neuroimage.2004.12.044 10.1016/j.neuroimage.2004.11.019 10.1002/ajmg.b.30825 10.1038/nn1201-1153 10.1016/j.neuroimage.2004.05.027 10.1002/mrm.10074 10.1093/brain/awn018 10.1126/science.1065103 10.1016/S0010-9452(13)80051-2 10.1002/nbm.781 10.4103/0019-5359.15085 10.1016/j.neuroimage.2008.01.063 10.1002/hbm.10102 10.1016/j.neuroimage.2004.04.025 10.1093/cercor/bhi016 10.1093/brain/112.3.799 10.1093/brain/122.5.963 10.1093/cercor/bhj127 10.1016/j.neuroimage.2007.10.060 10.1038/nn1014 10.1371/journal.pone.0000597 10.1016/j.neuroimage.2005.07.036 10.1016/j.tics.2005.03.005 10.1159/000063730 10.1016/S1053-8119(03)00199-X 10.1523/JNEUROSCI.3874-05.2006 10.1523/JNEUROSCI.1929-08.2008 10.1016/j.neulet.2006.04.006 10.1007/s004220000205 10.1126/science.289.5478.457 10.1103/PhysRevLett.94.018102 10.1073/pnas.090504197 10.1016/j.neuroimage.2004.08.050 10.1038/nn758 10.1016/j.physrep.2005.10.009 10.1093/cercor/bhl149 10.1002/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3 10.1038/nrn1119 10.1002/mrm.10144 10.1006/nimg.2001.1052 10.1093/brain/awh696 10.1103/PhysRevLett.87.198701 10.1073/pnas.0400087101 10.1073/pnas.96.18.10422 10.1176/ajp.150.1.130 10.1177/1073858406293182 10.1038/nn1075 10.1016/j.neuroimage.2007.02.012 10.1016/j.neuroimage.2006.01.006 10.1212/WNL.56.7.969 10.1093/cercor/bhn102 10.1371/journal.pcbi.0020095 10.1385/NI:2:2:145 10.1016/j.neuroimage.2005.08.051 10.1016/j.cmpb.2005.08.004 10.1006/nimg.2001.0978 10.1016/j.neuroimage.2006.09.018 10.1038/35065725 10.1016/j.neuroimage.2008.02.036 10.1371/journal.pcbi.0030017 10.1371/journal.pbio.0060159 10.1006/cogp.1997.0659 10.1093/brain/124.3.617 10.1126/science.298.5594.824 10.1006/nimg.2001.0994 10.1016/j.neuropsychologia.2003.11.022 |
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| Keywords | Brain Intelligence Humans Male Neural Pathways Intelligence Tests Nerve Net Adolescent Diffusion Magnetic Resonance Imaging Brain Mapping Adult Female Models, Neurological Cluster Analysis |
| Language | English |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceived and designed the experiments: Y. Li Y. Liu CY TJ. Analyzed the data: Y. Li Y. Liu JL CY. Contributed reagents/materials/analysis tools: WQ KL. Wrote the paper: Y. Li Y. Liu CY TJ. Data collection: Y. Liu JL WQ KL CY. |
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| References | R Plomin (ref43) 2001; 4 BW Waldmann (ref78) 1992; 48 YX Gong (ref63) 1982 G Esposito (ref8) 1999; 122 (Pt 5) R Milo (ref77) 2002; 298 PM Thompson (ref47) 2001; 4 M Lazar (ref81) 2005; 24 S Frangou (ref49) 2004; 23 M Song (ref6) 2008; 41 R Byrne (ref55) 1995 DJ Watts (ref18) 1998; 393 S Mori (ref23) 1999; 45 NC Andreasen (ref41) 1993; 150 QY Gong (ref50) 2005; 25 P Thottakara (ref66) 2006; 29 SH Eriksson (ref60) 2001; 124 S Achard (ref16) 2006; 26 S Boccaletti (ref72) 2006; 424 S Mori (ref33) 2002; 47 H Jiang (ref64) 2006; 81 D Le Bihan (ref28) 2003; 4 FJ Rugg-Gunn (ref61) 2002; 359 CC Hilgetag (ref38) 2004; 2 S Mori (ref71) 2002; 15 RJ Haier (ref4) 2005; 25 DM Weinstein (ref67) 1999 P Hagmann (ref30) 2008; 6 V Latora (ref74) 2001; 87 GJ Parker (ref25) 2002; 15 DS Bassett (ref21) 2008; 28 RE Jung (ref11) 2007; 30 MA Changizi (ref59) 2001; 84 M Lazar (ref69) 2000 SF Witelson (ref35) 1989; 112 (Pt 3) S Micheloyannis (ref19) 2006; 402 R Salvador (ref15) 2005; 15 TE Conturo (ref22) 1999; 96 VM Eguiluz (ref14) 2005; 94 CR Tench (ref26) 2002; 47 MA Koch (ref24) 2002; 16 SH Strogatz (ref37) 2001; 410 P Hagmann (ref29) 2007; 2 V Prabhakaran (ref1) 1997; 33 JL Gould (ref57) 2004; 14 SF Witelson (ref46) 2006; 129 JR Gray (ref2) 2003; 6 J Li (ref62) 2008; 150B Y Iturria-Medina (ref39) 2007; 36 J Duncan (ref51) 2000; 289 M Lazar (ref70) 2001 KH Lee (ref10) 2006; 29 N Tzourio-Mazoyer (ref65) 2002; 15 CJ Stam (ref17) 2007; 17 AL Reiss (ref42) 1996; 119 (Pt 5) G Roth (ref54) 2005; 9 Y Iturria-Medina (ref31) 2008; 40 DJ Tisserand (ref44) 2001; 56 Y He (ref20) 2007; 17 S Karande (ref79) 2005; 59 S Maslov (ref76) 2002; 296 O Sporns (ref12) 2004; 2 M Kaiser (ref53) 2006; 2 K Zhang (ref58) 2000; 97 R Colom (ref5) 2006; 31 T Fangmeier (ref9) 2006; 18 G Gong (ref32) 2009; 19 Y Liu (ref75) 2008; 131 KR Gibson (ref56) 2002; 59 DS Bassett (ref40) 2006; 12 A Barrat (ref73) 2004; 101 C Yu (ref34) 2008; 40 M Wilke (ref48) 2003; 20 DM Ivanovic (ref45) 2004; 42 MJ Boivin (ref7) 1992; 28 S Wakana (ref36) 2004; 230 M Lazar (ref68) 2003; 18 RJ Haier (ref3) 2004; 23 TE Behrens (ref27) 2003; 6 CJ Stam (ref13) 2004; 355 S Achard (ref52) 2007; 3 TE Behrens (ref80) 2007; 34 16848638 - PLoS Comput Biol. 2006 Jul 21;2(7):e95 16243544 - Neuroimage. 2006 Feb 1;29(3):868-78 12049867 - Lancet. 2002 May 18;359(9319):1748-51 18784304 - J Neurosci. 2008 Sep 10;28(37):9239-48 16122946 - Neuroimage. 2006 Jan 15;29(2):578-86 16339797 - Brain. 2006 Feb;129(Pt 2):386-98 11969331 - Neuroimage. 2002 May;16(1):241-50 9212721 - Cogn Psychol. 1997 Jun;33(1):43-63 9989633 - Ann Neurol. 1999 Feb;45(2):265-9 16512999 - J Cogn Neurosci. 2006 Mar;18(3):320-34 18299296 - Brain. 2008 Apr;131(Pt 4):945-61 15325390 - Neuroimage. 2004 Sep;23(1):425-33 15698136 - Phys Rev Lett. 2005 Jan 14;94(1):018102 15635061 - Cereb Cortex. 2005 Sep;15(9):1332-42 11979576 - Magn Reson Med. 2002 May;47(5):967-72 1499309 - Cortex. 1992 Jun;28(2):231-9 11988575 - Science. 2002 May 3;296(5569):910-3 10792049 - Proc Natl Acad Sci U S A. 2000 May 9;97(10):5621-6 17611629 - PLoS One. 2007;2(7):e597 18434203 - Neuroimage. 2008 Jul 1;41(3):1168-76 11723454 - Nat Neurosci. 2001 Dec;4(12):1153-4 14729226 - Neurosci Lett. 2004 Jan 23;355(1-2):25-8 11694885 - Nat Neurosci. 2001 Dec;4(12):1253-8 8931596 - Brain. 1996 Oct;119 ( Pt 5):1763-74 18567609 - Cereb Cortex. 2009 Mar;19(3):524-36 12592404 - Nat Neurosci. 2003 Mar;6(3):316-22 12778119 - Nat Rev Neurosci. 2003 Jun;4(6):469-80 16513370 - Neuroimage. 2006 Jul 1;31(3):1359-65 15866152 - Trends Cogn Sci. 2005 May;9(5):250-7 15627594 - Neuroimage. 2005 Jan 15;24(2):524-32 15365196 - Neuroinformatics. 2004;2(3):353-60 12097857 - Brain Behav Evol. 2002;59(1-2):10-20 15186759 - Curr Biol. 2004 May 25;14(10):R372-5 12808459 - Nat Neurosci. 2003 Jul;6(7):750-7 17655784 - Behav Brain Sci. 2007 Apr;30(2):135-54; discussion 154-87 18272400 - Neuroimage. 2008 Apr 15;40(3):1064-76 11906221 - Neuroimage. 2002 Apr;15(4):797-809 17079517 - Neuroscientist. 2006 Dec;12(6):512-23 18353685 - Neuroimage. 2008 May 1;40(4):1533-41 16399673 - J Neurosci. 2006 Jan 4;26(1):63-72 12399590 - Science. 2002 Oct 25;298(5594):824-7 1602026 - J Clin Psychol. 1992 May;48(3):360-3 11294939 - Neurology. 2001 Apr 10;56(7):969-71 10903207 - Science. 2000 Jul 21;289(5478):457-60 15734366 - Neuroimage. 2005 Mar;25(1):320-7 11258382 - Nature. 2001 Mar 8;410(6825):268-76 16413083 - Comput Methods Programs Biomed. 2006 Feb;81(2):106-16 16678344 - Neurosci Lett. 2006 Jul 24;402(3):273-7 10355679 - Brain. 1999 May;122 ( Pt 5):963-79 15093150 - Neuropsychologia. 2004;42(8):1118-31 18615479 - Am J Med Genet B Neuropsychiatr Genet. 2009 Apr 5;150B(3):375-80 15850735 - Neuroimage. 2005 May 1;25(4):1175-86 9623998 - Nature. 1998 Jun 4;393(6684):440-2 12632468 - Hum Brain Mapp. 2003 Apr;18(4):306-21 15319512 - Neuroinformatics. 2004;2(2):145-62 11222460 - Brain. 2001 Mar;124(Pt 3):617-26 11690461 - Phys Rev Lett. 2001 Nov 5;87(19):198701 17070705 - Neuroimage. 2007 Jan 1;34(1):144-55 8417555 - Am J Psychiatry. 1993 Jan;150(1):130-4 15805679 - Indian J Med Sci. 2005 Mar;59(3):95-103 14527581 - Neuroimage. 2003 Sep;20(1):202-15 11252638 - Biol Cybern. 2001 Mar;84(3):207-15 15528081 - Neuroimage. 2004 Nov;23(3):800-5 2731030 - Brain. 1989 Jun;112 ( Pt 3):799-835 15007165 - Proc Natl Acad Sci U S A. 2004 Mar 16;101(11):3747-52 17274684 - PLoS Comput Biol. 2007 Feb 2;3(2):e17 17204824 - Cereb Cortex. 2007 Oct;17(10):2407-19 11810663 - Magn Reson Med. 2002 Feb;47(2):215-23 14645885 - Radiology. 2004 Jan;230(1):77-87 16452642 - Cereb Cortex. 2007 Jan;17(1):92-9 11771995 - Neuroimage. 2002 Jan;15(1):273-89 12489096 - NMR Biomed. 2002 Nov-Dec;15(7-8):468-80 10468624 - Proc Natl Acad Sci U S A. 1999 Aug 31;96(18):10422-7 17466539 - Neuroimage. 2007 Jul 1;36(3):645-60 18597554 - PLoS Biol. 2008 Jul 1;6(7):e159 |
| References_xml | – volume: 18 start-page: 320 year: 2006 ident: ref9 article-title: FMRI evidence for a three-stage model of deductive reasoning. publication-title: J Cogn Neurosci doi: 10.1162/jocn.2006.18.3.320 – volume: 119 (Pt 5) start-page: 1763 year: 1996 ident: ref42 article-title: Brain development, gender and IQ in children. A volumetric imaging study. publication-title: Brain doi: 10.1093/brain/119.5.1763 – volume: 14 start-page: R372 year: 2004 ident: ref57 article-title: Animal cognition. publication-title: Curr Biol doi: 10.1016/j.cub.2004.05.008 – volume: 359 start-page: 1748 year: 2002 ident: ref61 article-title: Diffusion tensor imaging in refractory epilepsy. publication-title: Lancet doi: 10.1016/S0140-6736(02)08615-4 – volume: 355 start-page: 25 year: 2004 ident: ref13 article-title: Functional connectivity patterns of human magnetoencephalographic recordings: a ‘small-world’ network? publication-title: Neurosci Lett doi: 10.1016/j.neulet.2003.10.063 – volume: 2 start-page: 353 year: 2004 ident: ref38 article-title: Clustered organization of cortical connectivity. publication-title: Neuroinformatics doi: 10.1385/NI:2:3:353 – volume: 48 start-page: 360 year: 1992 ident: ref78 article-title: The relationship between intellectual ability and adult performance on the Trail Making Test and the Symbol Digit Modalities Test. publication-title: J Clin Psychol doi: 10.1002/1097-4679(199205)48:3<360::AID-JCLP2270480314>3.0.CO;2-P – volume: 30 start-page: 135 year: 2007 ident: ref11 article-title: The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence. publication-title: Behav Brain Sci doi: 10.1017/S0140525X07001185 – volume: 393 start-page: 440 year: 1998 ident: ref18 article-title: Collective dynamics of ‘small-world’ networks. publication-title: Nature doi: 10.1038/30918 – volume: 230 start-page: 77 year: 2004 ident: ref36 article-title: Fiber tract-based atlas of human white matter anatomy. publication-title: Radiology doi: 10.1148/radiol.2301021640 – volume: 25 start-page: 1175 year: 2005 ident: ref50 article-title: Voxel-based morphometry and stereology provide convergent evidence of the importance of medial prefrontal cortex for fluid intelligence in healthy adults. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.12.044 – volume: 25 start-page: 320 year: 2005 ident: ref4 article-title: The neuroanatomy of general intelligence: sex matters. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.11.019 – volume: 150B start-page: 375 year: 2008 ident: ref62 article-title: COMT val158met modulates association between brain white matter architecture and IQ. publication-title: Am J Med Genet B Neuropsychiatr Genet doi: 10.1002/ajmg.b.30825 – volume: 4 start-page: 1153 year: 2001 ident: ref43 article-title: Genes, brain and cognition. publication-title: Nat Neurosci doi: 10.1038/nn1201-1153 – volume: 23 start-page: 800 year: 2004 ident: ref49 article-title: Mapping IQ and gray matter density in healthy young people. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.05.027 – volume: 47 start-page: 215 year: 2002 ident: ref33 article-title: Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking. publication-title: Magn Reson Med doi: 10.1002/mrm.10074 – volume: 131 start-page: 945 year: 2008 ident: ref75 article-title: Disrupted small-world networks in schizophrenia. publication-title: Brain doi: 10.1093/brain/awn018 – volume: 296 start-page: 910 year: 2002 ident: ref76 article-title: Specificity and stability in topology of protein networks. publication-title: Science doi: 10.1126/science.1065103 – volume: 28 start-page: 231 year: 1992 ident: ref7 article-title: Verbal fluency and positron emission tomographic mapping of regional cerebral glucose metabolism. publication-title: Cortex doi: 10.1016/S0010-9452(13)80051-2 – volume: 15 start-page: 468 year: 2002 ident: ref71 article-title: Fiber tracking: principles and strategies - a technical review. publication-title: NMR Biomed doi: 10.1002/nbm.781 – volume: 59 start-page: 95 year: 2005 ident: ref79 article-title: Comparison of cognition abilities between groups of children with specific learning disability having average, bright normal and superior nonverbal intelligence. publication-title: Indian J Med Sci doi: 10.4103/0019-5359.15085 – volume: 40 start-page: 1533 year: 2008 ident: ref34 article-title: White matter tract integrity and intelligence in patients with mental retardation and healthy adults. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.01.063 – volume: 18 start-page: 306 year: 2003 ident: ref68 article-title: White matter tractography using diffusion tensor deflection. publication-title: Hum Brain Mapp doi: 10.1002/hbm.10102 – volume: 23 start-page: 425 year: 2004 ident: ref3 article-title: Structural brain variation and general intelligence. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.04.025 – volume: 15 start-page: 1332 year: 2005 ident: ref15 article-title: Neurophysiological architecture of functional magnetic resonance images of human brain. publication-title: Cereb Cortex doi: 10.1093/cercor/bhi016 – volume: 112 (Pt 3) start-page: 799 year: 1989 ident: ref35 article-title: Hand and sex differences in the isthmus and genu of the human corpus callosum. A postmortem morphological study. publication-title: Brain doi: 10.1093/brain/112.3.799 – volume: 122 (Pt 5) start-page: 963 year: 1999 ident: ref8 article-title: Context-dependent, neural system-specific neurophysiological concomitants of ageing: mapping PET correlates during cognitive activation. publication-title: Brain doi: 10.1093/brain/122.5.963 – volume: 17 start-page: 92 year: 2007 ident: ref17 article-title: Small-world networks and functional connectivity in Alzheimer's disease. publication-title: Cereb Cortex doi: 10.1093/cercor/bhj127 – volume: 40 start-page: 1064 year: 2008 ident: ref31 article-title: Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2007.10.060 – volume: 6 start-page: 316 year: 2003 ident: ref2 article-title: Neural mechanisms of general fluid intelligence. publication-title: Nat Neurosci doi: 10.1038/nn1014 – volume: 2 start-page: e597 year: 2007 ident: ref29 article-title: Mapping human whole-brain structural networks with diffusion MRI. publication-title: PLoS ONE doi: 10.1371/journal.pone.0000597 – volume: 29 start-page: 578 year: 2006 ident: ref10 article-title: Neural correlates of superior intelligence: stronger recruitment of posterior parietal cortex. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2005.07.036 – volume: 9 start-page: 250 year: 2005 ident: ref54 article-title: Evolution of the brain and intelligence. publication-title: Trends Cogn Sci doi: 10.1016/j.tics.2005.03.005 – volume: 59 start-page: 10 year: 2002 ident: ref56 article-title: Evolution of human intelligence: the roles of brain size and mental construction. publication-title: Brain Behav Evol doi: 10.1159/000063730 – start-page: 249 year: 1999 ident: ref67 article-title: Tensorlines: advection-diffusion based propagation through diffusion tensor fields. publication-title: IEEE Visualization Proc, San Francisco – volume: 20 start-page: 202 year: 2003 ident: ref48 article-title: Bright spots: correlations of gray matter volume with IQ in a normal pediatric population. publication-title: Neuroimage doi: 10.1016/S1053-8119(03)00199-X – volume: 26 start-page: 63 year: 2006 ident: ref16 article-title: A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. publication-title: J Neurosci doi: 10.1523/JNEUROSCI.3874-05.2006 – volume: 28 start-page: 9239 year: 2008 ident: ref21 article-title: Hierarchical organization of human cortical networks in health and schizophrenia. publication-title: J Neurosci doi: 10.1523/JNEUROSCI.1929-08.2008 – volume: 402 start-page: 273 year: 2006 ident: ref19 article-title: Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis. publication-title: Neurosci Lett doi: 10.1016/j.neulet.2006.04.006 – volume: 84 start-page: 207 year: 2001 ident: ref59 article-title: Principles underlying mammalian neocortical scaling. publication-title: Biol Cybern doi: 10.1007/s004220000205 – start-page: 482 year: 2000 ident: ref69 article-title: Axon tractography with tensorlines. – volume: 289 start-page: 457 year: 2000 ident: ref51 article-title: A neural basis for general intelligence. publication-title: Science doi: 10.1126/science.289.5478.457 – volume: 94 start-page: 018102 year: 2005 ident: ref14 article-title: Scale-free brain functional networks. publication-title: Phys Rev Lett doi: 10.1103/PhysRevLett.94.018102 – volume: 97 start-page: 5621 year: 2000 ident: ref58 article-title: A universal scaling law between gray matter and white matter of cerebral cortex. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.090504197 – volume: 24 start-page: 524 year: 2005 ident: ref81 article-title: Bootstrap white matter tractography (BOOT-TRAC). publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.08.050 – volume: 4 start-page: 1253 year: 2001 ident: ref47 article-title: Genetic influences on brain structure. publication-title: Nat Neurosci doi: 10.1038/nn758 – year: 1982 ident: ref63 article-title: Manual of modified Wechsler Adult Intelligence Scale (WAIS-RC) (in Chinese) – year: 1995 ident: ref55 article-title: The Thinking Ape: Evolutionary Origins of Intelligence – volume: 424 start-page: 175 year: 2006 ident: ref72 article-title: Complex networks: structure and dynamics. publication-title: Physics Reports doi: 10.1016/j.physrep.2005.10.009 – volume: 17 start-page: 2407 year: 2007 ident: ref20 article-title: Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. publication-title: Cereb Cortex doi: 10.1093/cercor/bhl149 – volume: 45 start-page: 265 year: 1999 ident: ref23 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: 4 start-page: 469 year: 2003 ident: ref28 article-title: Looking into the functional architecture of the brain with diffusion MRI. publication-title: Nat Rev Neurosci doi: 10.1038/nrn1119 – volume: 47 start-page: 967 year: 2002 ident: ref26 article-title: White matter mapping using diffusion tensor MRI. publication-title: Magn Reson Med doi: 10.1002/mrm.10144 – volume: 16 start-page: 241 year: 2002 ident: ref24 article-title: An investigation of functional and anatomical connectivity using magnetic resonance imaging. publication-title: Neuroimage doi: 10.1006/nimg.2001.1052 – volume: 129 start-page: 386 year: 2006 ident: ref46 article-title: Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors. publication-title: Brain doi: 10.1093/brain/awh696 – volume: 87 start-page: 198701 year: 2001 ident: ref74 article-title: Efficient behavior of small-world networks. publication-title: Phys Rev Lett doi: 10.1103/PhysRevLett.87.198701 – volume: 101 start-page: 3747 year: 2004 ident: ref73 article-title: The architecture of complex weighted networks. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0400087101 – volume: 96 start-page: 10422 year: 1999 ident: ref22 article-title: Tracking neuronal fiber pathways in the living human brain. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.96.18.10422 – volume: 150 start-page: 130 year: 1993 ident: ref41 article-title: Intelligence and brain structure in normal individuals. publication-title: Am J Psychiatry doi: 10.1176/ajp.150.1.130 – volume: 12 start-page: 512 year: 2006 ident: ref40 article-title: Small-world brain networks. publication-title: Neuroscientist doi: 10.1177/1073858406293182 – volume: 6 start-page: 750 year: 2003 ident: ref27 article-title: Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. publication-title: Nat Neurosci doi: 10.1038/nn1075 – volume: 36 start-page: 645 year: 2007 ident: ref39 article-title: Characterizing brain anatomical connections using diffusion weighted MRI and graph theory. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2007.02.012 – volume: 31 start-page: 1359 year: 2006 ident: ref5 article-title: Distributed brain sites for the g-factor of intelligence. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2006.01.006 – volume: 56 start-page: 969 year: 2001 ident: ref44 article-title: Head size and cognitive ability in nondemented older adults are related. publication-title: Neurology doi: 10.1212/WNL.56.7.969 – start-page: 506 year: 2001 ident: ref70 article-title: Error analysis of white matter tracking algorithms (streamline and tensorlines) for DT-MRI. – volume: 19 start-page: 524 year: 2009 ident: ref32 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: 2 start-page: e95 year: 2006 ident: ref53 article-title: Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems. publication-title: PLoS Comput Biol doi: 10.1371/journal.pcbi.0020095 – volume: 2 start-page: 145 year: 2004 ident: ref12 article-title: The small world of the cerebral cortex. publication-title: Neuroinformatics doi: 10.1385/NI:2:2:145 – volume: 29 start-page: 868 year: 2006 ident: ref66 article-title: Application of Brodmann's area templates for ROI selection in white matter tractography studies. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2005.08.051 – volume: 81 start-page: 106 year: 2006 ident: ref64 article-title: DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. publication-title: Comput Methods Programs Biomed doi: 10.1016/j.cmpb.2005.08.004 – volume: 15 start-page: 273 year: 2002 ident: ref65 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: 34 start-page: 144 year: 2007 ident: ref80 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: 410 start-page: 268 year: 2001 ident: ref37 article-title: Exploring complex networks. publication-title: Nature doi: 10.1038/35065725 – volume: 41 start-page: 1168 year: 2008 ident: ref6 article-title: Brain spontaneous functional connectivity and intelligence. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.02.036 – volume: 3 start-page: e17 year: 2007 ident: ref52 article-title: Efficiency and cost of economical brain functional networks. publication-title: PLoS Comput Biol doi: 10.1371/journal.pcbi.0030017 – volume: 6 start-page: e159 year: 2008 ident: ref30 article-title: Mapping the structural core of human cerebral cortex. publication-title: PLoS Biol doi: 10.1371/journal.pbio.0060159 – volume: 33 start-page: 43 year: 1997 ident: ref1 article-title: Neural substrates of fluid reasoning: an fMRI study of neocortical activation during performance of the Raven's Progressive Matrices Test. publication-title: Cognit Psychol doi: 10.1006/cogp.1997.0659 – volume: 124 start-page: 617 year: 2001 ident: ref60 article-title: Diffusion tensor imaging in patients with epilepsy and malformations of cortical development. publication-title: Brain doi: 10.1093/brain/124.3.617 – volume: 298 start-page: 824 year: 2002 ident: ref77 article-title: Network motifs: simple building blocks of complex networks. publication-title: Science doi: 10.1126/science.298.5594.824 – volume: 15 start-page: 797 year: 2002 ident: ref25 article-title: Initial demonstration of in vivo tracing of axonal projections in the macaque brain and comparison with the human brain using diffusion tensor imaging and fast marching tractography. publication-title: Neuroimage doi: 10.1006/nimg.2001.0994 – volume: 42 start-page: 1118 year: 2004 ident: ref45 article-title: Head size and intelligence, learning, nutritional status and brain development. Head, IQ, learning, nutrition and brain. publication-title: Neuropsychologia doi: 10.1016/j.neuropsychologia.2003.11.022 – reference: 11771995 - Neuroimage. 2002 Jan;15(1):273-89 – reference: 11988575 - Science. 2002 May 3;296(5569):910-3 – reference: 17611629 - PLoS One. 2007;2(7):e597 – reference: 16122946 - Neuroimage. 2006 Jan 15;29(2):578-86 – reference: 11969331 - Neuroimage. 2002 May;16(1):241-50 – reference: 11694885 - Nat Neurosci. 2001 Dec;4(12):1253-8 – reference: 9623998 - Nature. 1998 Jun 4;393(6684):440-2 – reference: 15325390 - Neuroimage. 2004 Sep;23(1):425-33 – reference: 11810663 - Magn Reson Med. 2002 Feb;47(2):215-23 – reference: 15007165 - Proc Natl Acad Sci U S A. 2004 Mar 16;101(11):3747-52 – reference: 15734366 - Neuroimage. 2005 Mar;25(1):320-7 – reference: 16399673 - J Neurosci. 2006 Jan 4;26(1):63-72 – reference: 16848638 - PLoS Comput Biol. 2006 Jul 21;2(7):e95 – reference: 11294939 - Neurology. 2001 Apr 10;56(7):969-71 – reference: 12399590 - Science. 2002 Oct 25;298(5594):824-7 – reference: 17274684 - PLoS Comput Biol. 2007 Feb 2;3(2):e17 – reference: 12632468 - Hum Brain Mapp. 2003 Apr;18(4):306-21 – reference: 16243544 - Neuroimage. 2006 Feb 1;29(3):868-78 – reference: 9212721 - Cogn Psychol. 1997 Jun;33(1):43-63 – reference: 16452642 - Cereb Cortex. 2007 Jan;17(1):92-9 – reference: 10792049 - Proc Natl Acad Sci U S A. 2000 May 9;97(10):5621-6 – reference: 12489096 - NMR Biomed. 2002 Nov-Dec;15(7-8):468-80 – reference: 18434203 - Neuroimage. 2008 Jul 1;41(3):1168-76 – reference: 12778119 - Nat Rev Neurosci. 2003 Jun;4(6):469-80 – reference: 10355679 - Brain. 1999 May;122 ( Pt 5):963-79 – reference: 15635061 - Cereb Cortex. 2005 Sep;15(9):1332-42 – reference: 18299296 - Brain. 2008 Apr;131(Pt 4):945-61 – reference: 15528081 - Neuroimage. 2004 Nov;23(3):800-5 – reference: 17466539 - Neuroimage. 2007 Jul 1;36(3):645-60 – reference: 18597554 - PLoS Biol. 2008 Jul 1;6(7):e159 – reference: 12097857 - Brain Behav Evol. 2002;59(1-2):10-20 – reference: 1602026 - J Clin Psychol. 1992 May;48(3):360-3 – reference: 11252638 - Biol Cybern. 2001 Mar;84(3):207-15 – reference: 11723454 - Nat Neurosci. 2001 Dec;4(12):1153-4 – reference: 16513370 - Neuroimage. 2006 Jul 1;31(3):1359-65 – reference: 16512999 - J Cogn Neurosci. 2006 Mar;18(3):320-34 – reference: 11258382 - Nature. 2001 Mar 8;410(6825):268-76 – reference: 16678344 - Neurosci Lett. 2006 Jul 24;402(3):273-7 – reference: 15365196 - Neuroinformatics. 2004;2(3):353-60 – reference: 14729226 - Neurosci Lett. 2004 Jan 23;355(1-2):25-8 – reference: 1499309 - Cortex. 1992 Jun;28(2):231-9 – reference: 8931596 - Brain. 1996 Oct;119 ( Pt 5):1763-74 – reference: 12049867 - Lancet. 2002 May 18;359(9319):1748-51 – reference: 11222460 - Brain. 2001 Mar;124(Pt 3):617-26 – reference: 15866152 - Trends Cogn Sci. 2005 May;9(5):250-7 – reference: 12808459 - Nat Neurosci. 2003 Jul;6(7):750-7 – reference: 15093150 - Neuropsychologia. 2004;42(8):1118-31 – reference: 15186759 - Curr Biol. 2004 May 25;14(10):R372-5 – reference: 14645885 - Radiology. 2004 Jan;230(1):77-87 – reference: 17079517 - Neuroscientist. 2006 Dec;12(6):512-23 – reference: 10903207 - Science. 2000 Jul 21;289(5478):457-60 – reference: 18272400 - Neuroimage. 2008 Apr 15;40(3):1064-76 – reference: 15805679 - Indian J Med Sci. 2005 Mar;59(3):95-103 – reference: 14527581 - Neuroimage. 2003 Sep;20(1):202-15 – reference: 15319512 - Neuroinformatics. 2004;2(2):145-62 – reference: 8417555 - Am J Psychiatry. 1993 Jan;150(1):130-4 – reference: 12592404 - Nat Neurosci. 2003 Mar;6(3):316-22 – reference: 17655784 - Behav Brain Sci. 2007 Apr;30(2):135-54; discussion 154-87 – reference: 18784304 - J Neurosci. 2008 Sep 10;28(37):9239-48 – reference: 11690461 - Phys Rev Lett. 2001 Nov 5;87(19):198701 – reference: 9989633 - Ann Neurol. 1999 Feb;45(2):265-9 – reference: 17204824 - Cereb Cortex. 2007 Oct;17(10):2407-19 – reference: 16413083 - Comput Methods Programs Biomed. 2006 Feb;81(2):106-16 – reference: 15698136 - Phys Rev Lett. 2005 Jan 14;94(1):018102 – reference: 18615479 - Am J Med Genet B Neuropsychiatr Genet. 2009 Apr 5;150B(3):375-80 – reference: 15627594 - Neuroimage. 2005 Jan 15;24(2):524-32 – reference: 11906221 - Neuroimage. 2002 Apr;15(4):797-809 – reference: 17070705 - Neuroimage. 2007 Jan 1;34(1):144-55 – reference: 18353685 - Neuroimage. 2008 May 1;40(4):1533-41 – reference: 15850735 - Neuroimage. 2005 May 1;25(4):1175-86 – reference: 10468624 - Proc Natl Acad Sci U S A. 1999 Aug 31;96(18):10422-7 – reference: 2731030 - Brain. 1989 Jun;112 ( Pt 3):799-835 – reference: 11979576 - Magn Reson Med. 2002 May;47(5):967-72 – reference: 18567609 - Cereb Cortex. 2009 Mar;19(3):524-36 – reference: 16339797 - Brain. 2006 Feb;129(Pt 2):386-98 |
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| Snippet | Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported... Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported... |
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| SubjectTerms | Adolescent Adult Brain Brain - anatomy & histology Brain - physiology Brain Mapping Cluster Analysis Computational Biology/Computational Neuroscience Diffusion Magnetic Resonance Imaging Female Humans Intellect Intelligence - physiology Intelligence levels Intelligence Tests Male Models, Neurological Nerve Net - anatomy & histology Neural circuitry Neural Pathways - anatomy & histology Neuroscience/Cognitive Neuroscience NMR Nuclear magnetic resonance Physiological aspects Radiology and Medical Imaging/Magnetic Resonance Imaging Studies |
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| Title | Brain Anatomical Network and Intelligence |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/19492086 https://www.proquest.com/docview/67317969 https://pubmed.ncbi.nlm.nih.gov/PMC2683575 https://doaj.org/article/e9845f9fc51a499288623c6799249ff3 http://dx.doi.org/10.1371/journal.pcbi.1000395 |
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