Establishing a link between sex-related differences in the structural connectome and behaviour

Philosophical Transactions of the Royal Society B: Biological Sciences

Volumn 371, Issue 1688, 2016, Pages

  Tunç, Birkan ^a   Solmaz, Berkan ^a   Parker, Drew ^a   Satterthwaite, Theodore D ^b   Elliott, Mark A ^b   Calkins, Monica E ^b   Ruparel, Kosha ^b   Gur, Raquel E ^b   Gur, Ruben C ^b   Verma, Ragini ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Behaviour; Connectome; Diffusion imaging; Gender; Sex; Structural connectivity

Indexed keywords

BEHAVIORAL RESPONSE; BRAIN; CONNECTIVITY; GENDER; HUMAN BEHAVIOR; IMAGING METHOD; MAP; MULTIVARIATE ANALYSIS; SEX-RELATED DIFFERENCE; YOUNG POPULATION;

ADOLESCENT; ANIMAL; BRAIN; CHILD; CONNECTOME; FEMALE; HUMAN; MALE; MULTIVARIATE ANALYSIS; NERVE CELL NETWORK; PHYSIOLOGY; PROCEDURES; SEX DIFFERENCE; YOUNG ADULT;

ADOLESCENT; ANIMALS; BRAIN; CHILD; CONNECTOME; FEMALE; HUMANS; MALE; MULTIVARIATE ANALYSIS; NERVE NET; SEX FACTORS; YOUNG ADULT;

EID: 84956672422     PISSN: 09628436     EISSN: 14712970     Source Type: Journal    
DOI: 10.1098/rstb.2015.0111     Document Type: Article

References (52)

1. Halpern DF, Benbow CP, Geary DC, Gur RC, Hyde JS, Gernsbacher MA. 2007 The science of sex differences in science and mathematics. Psychol. Sci. Public Interest 8, 1-51.(doi:10.1111/j.1529-1006.2007.00032.x)
2. Hines M. 2010 Sex-related variation in human behavior and the brain. Trends Cogn. Sci. 14, 448-456. (doi:10.1016/j.tics.2010.07.005)
3. Moreno-Briseño P, Díaz R, Campos-Romo A, Fernandez-Ruiz J. 2010 Sex-related differences in motor learning and performance. Behav. Brain Funct. 6, 74. (doi:10.1186/1744-9081-6-74)
4. Thomas JR, French KE. 1985 Gender differences across age in motor performance: a meta-analysis. Psychol. Bull. 98, 260-282. (doi:10.1037/0033-2909.98.2.260)
5. Linn MC, Petersen AC. 1985 Emergence and characterization of sex differences in spatial ability: a meta-analysis. Child Dev. 56, 1479-1498. (doi:10.2307/1130467)
6. Voyer D, Voyer S, Bryden MP. 1995 Magnitude of sex differences in spatial abilities: a meta-analysis and consideration of critical variables. Psychol. Bull. 117, 250-270. (doi:10.1037/0033-2909.117.2.250)
7. Hedges LV, Nowell A. 1995 Sex differences in mental test scores, variability, and numbers of high-scoring individuals. Science 269, 41-45. (doi:10.1126/science.7604277)
8. Saykin AJ, Gur RC, Gur RE, Shtasel DL, Flannery KA, Mozley LH, Malamut BL, Watson B, Mozley PD. 1995 Normative neuropsychological test performance: effects of age, education, gender and ethnicity. Appl. Neuropsychol. 2, 79-88. (doi:10.1207/s15324826an0202_5)
9. Erwin RJ, Gur RC, Gur RE, Skolnick B, Mawhinney-Hee M, Smailis J. 1992 Facial emotion discrimination. I. Task construction and behavioral findings in normal subjects. Psychiatry Res. 42, 231-240. (doi:10.1016/0165-1781(92)90115-J)
10. Williams LM, Mathersul D, Palmer DM, Gur RC, Gur RE, Gordon E. 2009 Explicit identification and implicit recognition of facial emotions. I. Age effects in males and females across 10 decades. J. Clin. Exp. Neuropsychol. 31, 257-277. (doi:10.1080/13803390802255635)
11. Gur RC et al. 2012 Age group and sex differences in performance on a computerized neurocognitive battery in children age 8 - 21. Neuropsychology 26, 251-265. (doi:10.1037/a0026712)
12. Gur RC, Turetsky BI, Matsui M, Yan M, Bilker W, Hughett P, Gur RE. 1999 Sex differences in brain gray and white matter in healthy young adults: correlations with cognitive performance. J. Neurosci. 19, 4065-4072.
13. Allen JS, Damasio H, Grabowski TJ, Bruss J, Zhang W. 2003 Sexual dimorphism and asymmetries in the gray-white composition of the human cerebrum. Neuroimage 18, 880-894. (doi:10.1016/S1053-8119(03)00034-X)
14. Szeszko PR, Vogel J, Ashtari M, Malhotra AK, Bates J, Kane JM, Bilder RM, Frevert T, Lim K. 2003 Sex differences in frontal lobe white matter microstructure: a DTI study. Neuroreport 14, 2469-2473. (doi:10.1097/01.wnr.0000099475.09597.23)
15. Schmithorst VJ, Holland SK, Dardzinski BJ. 2008 Developmental differences in white matter architecture between boys and girls. Hum. Brain Mapp. 29, 696-710 (doi:10.1002/hbm.20431)
16. Satterthwaite TD et al. 2014 Linked sex differences in cognition and functional connectivity in youth. Cereb. Cortex 25, 2383-2394. (doi:10.1093/cercor/bhu036)
17. Ingalhalikar M et al. 2014 Sex differences in the structural connectome of the human brain. Proc. Natl Acad. Sci. USA 111, 823-828. (doi:10.1073/pnas.1316909110)
18. Andreasen NC, Flaum M, Swayze V, O’Leary DS, Alliger R, Cohen G, Ehrhardt J, Yuh WT. 1993 Intelligence and brain structure in normal individuals. Am. J. Psychiatry 150, 130-134. (doi:10.1176/ajp.150.1.130)
19. Hsu J-L, Leemans A, Bai C-H, Lee C-H, Tsai Y-F, Chiu H-C, Chen W-H. 2008 Gender differences and agerelated white matter changes of the human brain: a diffusion tensor imaging study. Neuroimage 39, 566-577. (doi:10.1016/j.neuroimage.2007.09.017)
20. Herting MM, Maxwell EC, Irvine C, Nagel BJ. 2011 The impact of sex, puberty, and hormones on white matter microstructure in adolescents. Cereb. Cortex 22, 1979-1992. (doi:10.1093/cercor/bhr246)
21. Bava S, Boucquey V, Goldenberg D, Thayer RE, Ward M, Jacobus J, Tapert SF. 2011 Sex differences in adolescent white matter architecture. Brain Res. 1375, 41-48. (doi:10.1016/j.brainres.2010.12.051)
22. Kanaan RA, Allin M, Picchioni M, Barker GJ, Daly E, Shergill SS, Woolley J, McGuire PK. 2012 Gender differences in white matter microstructure. PLoS ONE 7, e38272. (doi:10.1371/journal.pone.0038272)
23. Clayden JD, Jentschke S, Muñoz M, Cooper JM, Chadwick MJ, Banks T, Clark CA, Vargha-Khadem F. 2012 Normative development of white matter tracts: similarities and differences in relation to age, gender, and intelligence. Cereb. Cortex 22, 1738-1747. (doi:10.1093/cercor/bhr243)
24. Basser PJ, Mattiello J, Lebihan D. 1994 MR diffusion tensor spectroscopy and imaging. Biophys. J. 66, 259-267. (doi:10.1016/S0006-3495(94)80775-1)
25. Sporns O, Tononi G, Kötter R. 2005 The human connectome: a structural description of the human brain. PLoS Comput. Biol. 1, e42. (doi:10.1371/journal.pcbi.0010042)
26. Girvan M, Newman MEJ. 2002 Community structure in social and biological networks. Proc. Natl Acad. Sci. USA 99, 7821-7826. (doi:10.1073/pnas.122653799)
27. Van den Heuvel MP, Sporns O. 2011 Rich-club organization of the human connectome. J. Neurosci. 31, 15775-15 786. (doi:10.1523/JNEUROSCI.3539-11.2011)
28. Schwarz AJ, Gozzi A, Bifone A. 2008 Community structure and modularity in networks of correlated brain activity. Magn. Reson. Imaging 26, 914-920. (doi:10.1016/j.mri.2008.01.048)
29. Tononi G, Sporns O, Edelman GM. 1994 A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc. Natl Acad. Sci. USA 91, 5033-5037. (doi:10.1073/pnas.91.11.5033)
30. Ghanbari Y, Smith AR, Schultz RT, Verma R. 2014 Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding. Med. Image Anal. 18, 1337-1348. (doi:10.1016/j.media.2014.06.006)
31. Tunç B, Shankar V, Parker D, Schultz RT, Verma R. 2015 Towards a quantified network portrait of a population. In Information processing in medical imaging (IPMI) (eds S Ourselin, DC Alexander, C-F Westin, MJ Cardoso), pp 650-661. Berlin, Germany: Springer.
32. Satterthwaite TD et al. 2014 Impact of puberty on the evolution of cerebral perfusion during adolescence. Proc. Natl Acad. Sci. USA 111, 8643-8648. (doi:10.1073/pnas.1400178111)
33. Satterthwaite TD et al. 2014 Neuroimaging of the Philadelphia Neurodevelopmental Cohort. Neuroimage 86, 544-553. (doi:10.1016/j.neuroimage.2013.07.064)
34. Rubinov M, Sporns O. 2010 Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52, 1059-1069. (doi:10.1016/j.neuroimage.2009.10.003)
35. Blondel VD, Guillaume J-L, Lambiotte R, Lefebvre E. 2008 Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 10, P10008. (doi:10.1088/1742-5468/2008/10/P10008)
36. Legato MJ. 2009 Principles of gender-specific medicine, 2nd edn. New York, NY: Academic Press.
37. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O. 2008 Mapping the structural core of human cerebral cortex. PLoS Biol. 6, e159. (doi:10.1371/journal.pbio.0060159)
38. Greicius MD, Krasnow B, Reiss AL, Menon V. 2003 Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl Acad. Sci. USA 100, 253-258. (doi:10.1073/pnas.0135058100)
39. Power JD et al. 2011 Functional network organization of the human brain. Neuron 72, 665-678. (doi:10.1016/j.neuron.2011.09.006)
40. Heine L et al. 2012 Resting state networks and consciousness: alterations of multiple resting state network connectivity in physiological, pharmacological, and pathological consciousness states. Front. Psychol. 3, 295. (doi:10.3389/fpsyg.2012.00295)
41. Adolphs R. 2009 The social brain: neural basis of social knowledge. Annu. Rev. Psychol. 60, 693-716. (doi:10.1146/annurev.psych.60.110707.163514)
42. Kohls G et al. 2013 The nucleus accumbens is involved in both the pursuit of social reward and the avoidance of social punishment. Neuropsychologia 51, 2062-2069. (doi:10.1016/j.neuropsychologia.2013.07.020)
43. Barrett LF, Satpute AB. 2013 Large-scale brain networks in affective and social neuroscience: towards an integrative functional architecture of the brain. Curr. Opin. Neurobiol. 23, 361-372. (doi:10.1016/j.conb.2012.12.012)
44. Chevallier C, Kohls G, Troiani V, Brodkin ES, Schultz RT. 2012 The social motivation theory of autism. Trends Cogn. Sci. 16, 231-239. (doi:10.1016/j.tics.2012.02.007)
45. Gur RC, Richard J, Hughett P, Calkins ME, Macy L, Bilker WB, Brensinger C, Gur RE. 2010 A cognitive neuroscience-based computerized battery for efficient measurement of individual differences: standardization and initial construct validation. J. Neurosci. Methods 187, 254-262. (doi:10.1016/j.jneumeth.2009.11.017)
46. Calkins ME et al. 2014 The psychosis spectrum in a young U.S. community sample: findings from the Philadelphia Neurodevelopmental Cohort. World Psychiatry 13, 296-305. (doi:10.1002/wps.20152)
47. Alexander-Bloch A, Lambiotte R, Roberts B, Giedd J, Gogtay N, Bullmore E. 2012 The discovery of population differences in network community 10 structure: new methods and applications to brain functional networks in schizophrenia. Neuroimage 59, 3889-3900. (doi:10.1016/j.neuroimage.2011.11.035)
48. Kumar A, Rai P, Daume H. 2011 Co-regularized multi-view spectral clustering. In Advances in Neural Information Processing Systems 24: Proc. 25th Annual Conference on Neural Information Processing Systems, 12-15 December 2011, Granada, Spain (eds J Shawe-Taylor, RS Zemel, PL Bartlett, F Pereira, KQ Weinberger), pp 1413-1421. Red Hook, NY: Curran Associates.
49. Gu S, Pasqualetti F, Cieslak M, Grafton ST, Bassett DS. 2014 Controllability of brain networks. (http://arxiv.org/abs/1406.5197v1)
50. Cortes C, Vapnik VN. 1995 Support-vector networks. Mach. Learn. 20, 273-297. (doi:10.1007/BF00994018)
51. Benjamini Y, Hochberg Y. 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing. JR. Stat. Soc. Ser. B 57, 289-300.
52. Alpaydin E. 2010 Introduction to machine learning, 2nd edn. Cambridge, MA: MIT Press.