The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index.
Heritability of fractional anisotropy in human white matter: A comparison of Human Connectome Project and ENIGMA-DTI data
Open accessAbstract
The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p<10(-5)), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Cortical thickness and surface area also have considerable genetic influences that vary by cortical region, but interestingly share little shared genetic variance between them, indicating that these two aspects of cortical volume are regulated by different sets of genetic influences 144, 145.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [144]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
nlme : Linear and nonlinear mixed effects models
DebRoy, S. (2006) · Medical Entomology and Zoology · Cited by 10,009
nlme: Linear and Nonlinear Mixed Effects Models
Pinheiro, J., R Core Team, & Bates, D. (1999) · doi:10.32614/cran.package.nlme · Cited by 6,867
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
Smith, S. M., Jenkinson, M., Johansen‐Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., Watkins, K. E., Ciccarelli, O., Cader, M. Z., Matthews, P. M., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.024 · Cited by 6,598
Self-citationMR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253
Self-citationThe Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods
Jack, C. R., Bernstein, M. A., Fox, N. C., Thompson, P., Alexander, G., Harvey, D., Borowski, B., Britson, P. J., L. Whitwell, J., Ward, C., et al. (2008) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21049 · Cited by 4,347
Self-citationBasser, P. J., & Pierpaoli, C. (1996) · Journal of Magnetic Resonance, Series B · doi:10.1006/jmrb.1996.0086 · Cited by 4,306
Characterization and propagation of uncertainty in diffusion-weighted MR imaging
Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen‐Berg, H., Nunes, R. G., Clare, S., Matthews, P. M., Brady, J. M., & Smith, S. M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10609 · Cited by 3,038
Self-citationMultipoint Quantitative-Trait Linkage Analysis in General Pedigrees
Almasy, L. A., & Blangero, J. (1998) · The American Journal of Human Genetics · doi:10.1086/301844 · Cited by 3,021
Self-citation
Cited by
Sorted by citations
Imaging structural and functional brain development in early childhood
Gilmore, J. H., Knickmeyer, R. C., & Gao, W. (2018) · Nature Reviews Neuroscience · doi:10.1038/nrn.2018.1 · Cited by 1,013
Kelly, S., Jahanshad, N., Zalesky, A., Kochunov, P., Agartz, I., Alloza, C., Andreassen, O. A., Arango, C., Banaj, N., Bouix, S., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.170 · Cited by 701
Self-citationAndreu-Pérez, J., Poon, C. C. Y., Merrifield, R. D., Wong, S. T. C., & Yang, G. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2450362 · Cited by 728
Eliot, L., Ahmed, A., Khan, H., & Patel, J. Y. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.02.026 · Cited by 379
van Velzen, L. S., Kelly, S., Isaev, D., Aleman, A., Aftanas, L. I., Bauer, J., Baune, B. T., Brak, I. V., Carballedo, A., Connolly, C. G., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0477-2 · Cited by 369
Self-citationLebel, C., Treit, S., & Beaulieu, C. (2019) · NMR in Biomedicine · doi:10.1002/nbm.3778 · Cited by 379
Koshiyama, D., Fukunaga, M., Okada, N., Morita, K., Nemoto, K., Usui, K., Yamamori, H., Yasuda, Y., Fujimoto, M., Kudo, N., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0553-7 · Cited by 283
Self-citationSchmaal, L., Pozzi, E., Ho, T. C., van Velzen, L. S., Veer, I. M., Opel, N., Someren, E. J. W. V., Han, L. K. M., Aftanas, L., Aleman, A., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0842-6 · Cited by 261
Self-citationCommon genetic variation influencing human white matter microstructure
Zhao, B., Li, T., Yang, Y., Wang, X., Luo, T., Shan, Y., Zhu, Z., Xiong, D., Hauberg, M. E., Bendl, J. M., et al. (2021) · Science · doi:10.1126/science.abf3736 · Cited by 222
White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study
Hatton, S. N., Huynh, K. H., Bonilha, L., Abela, E., Alhusaini, S., Altmann, A., Alvim, M. K. M., Balachandra, A. R., Bartolini, E., Bender, B., et al. (2020) · Brain · doi:10.1093/brain/awaa200 · Cited by 238
Self-citationENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide
Thompson, P. M., Andreassen, O. A., Vásquez, A. A., Bearden, C. E., Boedhoe, P. S. W., Brouwer, R. M., Buckner, R. L., Buitelaar, J. K., Bulayeva, K., Cannon, D. M., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.057 · Cited by 178
Self-citationTamnes, C. K., Roalf, D. R., Goddings, A., & Lebel, C. A. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.12.002 · Cited by 164
Zhao, B., Zhang, J., Ibrahim, J. G., Luo, T., Santelli, R., Li, Y., Li, T., Shan, Y., Zhu, Z., Zhou, F., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0569-z · Cited by 150
Self-citationThe visual word form area (VWFA) is part of both language and attention circuitry
Chen, L., Wassermann, D., Abrams, D. A., Kochalka, J., Gallardo, G., & Menon, V. (2019) · Nature Communications · doi:10.1038/s41467-019-13634-z · Cited by 165
Yeh, F.-C., Vettel, J. M., Singh, A., Poczos, B., Grafton, S. T., Erickson, K. I., Tseng, W.-Y. I., & Verstynen, T. D. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005203 · Cited by 151
Association of White Matter With Core Cognitive Deficits in Patients With Schizophrenia
Kochunov, P., Coyle, T. R., Rowland, L. M., Jahanshad, N., Thompson, P. M., Kelly, S., Du, X. M., Sampath, H., Bruce, H. A., Chiappelli, J., et al. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.2228 · Cited by 151
Self-citationIndividual Brain Charting, a high-resolution fMRI dataset for cognitive mapping
Pinho, A. L., Amadon, A., Ruest, T., Fabre, M., Dohmatob, E., Denghien, I., Ginisty, C., Becuwe-Desmidt, S., Roger, S., Laurier, L., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.105 · Cited by 158
Shu, N., Wang, X., Bi, Q., Zhao, T., & Han, Y. (2018) · Radiology · doi:10.1148/radiol.2017162696 · Cited by 135
The heritability of multi-modal connectivity in human brain activity
Colclough, G. L., Smith, S. M., Nichols, T. E., Winkler, A. M., Sotiropoulos, S. N., Glasser, M. F., Essen, D. C. V., & Woolrich, M. W. (2017) · eLife · doi:10.7554/elife.20178 · Cited by 127
Self-citationBrain effective connectivity during motor-imagery and execution following stroke and rehabilitation
Bajaj, S., Butler, A. J., Drake, D. F., & Dhamala, M. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.06.006 · Cited by 134
Heritability and reliability of automatically segmented human hippocampal formation subregions
Whelan, C. D., Hibar, D. P., van Velzen, L. S., Zannas, A. S., Carrillo‐Roa, T., McMahon, K. L., Prasad, G., Kelly, S., Faskowitz, J., de Zubicaray, G. I., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.039 · Cited by 124
Self-citationHigh-resolution connectomic fingerprints: Mapping neural identity and behavior
Sina Mansour, L., Tian, Y., Yeo, B. T. T., Cropley, V., & Zalesky, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2020.117695 · Cited by 110
Advances in microstructural diffusion neuroimaging for psychiatric disorders
Pasternak, O., Kelly, S., Sydnor, V. J., & Shenton, M. E. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.051 · Cited by 116
Reus, L. M., Shen, X., Gibson, J., Wigmore, E. M., Ligthart, L., Adams, M. J., Davies, G., Cox, S. R., Hagenaars, S. P., Bastin, M. E., et al. (2017) · Scientific Reports · doi:10.1038/srep42140 · Cited by 98
Self-citationThe reliability and heritability of cortical folds and their genetic correlations across hemispheres
Pizzagalli, F., Auzias, G., Yang, Q., Mathias, S. R., Faskowitz, J., Boyd, J., Amini, A., Rivière, D., McMahon, K. L., de Zubicaray, G. I., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-01163-1 · Cited by 104
Self-citationZhang, S., & Arfanakis, K. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.046 · Cited by 99
Popuri, K., Ma, D., Wang, L., & Beg, M. F. (2020) · Human Brain Mapping · doi:10.1002/hbm.25115 · Cited by 96
Iacono, W. G., Heath, A. C., Hewitt, J. K., Neale, M. C., Banich, M. T., Luciana, M. M., Madden, P. A., Barch, D. M., & Bjork, J. M. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.09.001 · Cited by 94
Mapping population-based structural connectomes
Zhang, Z., Descoteaux, M., Zhang, J., Girard, G., Chamberland, M., Dunson, D. B., Srivastava, A., & Hongtu Zhu, B. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.064 · Cited by 93
Genetic variations influence brain changes in patients with attention-deficit hyperactivity disorder
Yadav, S. K., Bhat, A. A., Hashem, S., Nisar, S., Kamal, M., Syed, N., Temanni, M.-R., Gupta, R. K., Kamran, S., Azeem, M. W., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01473-w · Cited by 108
Kochunov, P., Hong, L. E., Dennis, E. L., Morey, R. A., Tate, D. F., Wilde, E. A., Logue, M. W., Kelly, S., Donohoe, G. J., Favre, P., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.24998 · Cited by 89
Self-citationPohl, K. M., Sullivan, E. V., Rohlfing, T., Chu, W., Kwon, D., Nichols, B. N., Zhang, Y., Brown, S. A., Tapert, S. F., Cummins, K., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.061 · Cited by 85
Mega‐analysis methods in ENIGMA : The experience of the generalized anxiety disorder working group
Zugman, A., Harrewijn, A., Cardinale, E. M., Zwiebel, H., Freitag, G. F., Werwath, K. E., Bas‐Hoogendam, J. M., Groenewold, N. A., Aghajani, M., Hilbert, K., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25096 · Cited by 83
Self-citationGenetic Influence on the Sulcal Pits: On the Origin of the First Cortical Folds
Guen, Y. L., Auzias, G., Leroy, F., Noulhiane, M., Dehaene‐Lambertz, G., Duchesnay, É., Mangin, J., Coulon, O., & Frouin, V. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx098 · Cited by 80
Grey and white matter microstructure is associated with polygenic risk for schizophrenia
Stauffer, E.-M., Bethlehem, R. A. I., Warrier, V., Murray, G. K., Romero-García, R., Seidlitz, J., & Bullmore, E. T. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01260-5 · Cited by 75
Koenis, M. M. G., Brouwer, R. M., Swagerman, S. C., van Soelen, I. L. C., Boomsma, D. I., & Pol, H. E. H. (2017) · Human Brain Mapping · doi:10.1002/hbm.23885 · Cited by 72
Self-citationMulder, D., Aarts, E., Vásquez, A. A., & Bloemendaal, M. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02146-4 · Cited by 70
Sex is a defining feature of neuroimaging phenotypes in major brain disorders
Salminen, L. E., Tubi, M. A., Bright, J. K., Thomopoulos, S. I., Wieand, A., & Thompson, P. M. (2021) · Human Brain Mapping · doi:10.1002/hbm.25438 · Cited by 61
Self-citationKochunov, P., Ganjgahi, H., Winkler, A. M., Kelly, S., Shukla, D. K., Du, X. M., Jahanshad, N., Rowland, L. M., Sampath, H., Patel, B., et al. (2016) · Human Brain Mapping · doi:10.1002/hbm.23336 · Cited by 63
Self-citationVuoksimaa, E., Panizzon, M. S., Hagler Jr, D. J., Hatton, S. N., Fennema‐Notestine, C., Rinker, D., Eyler, L. T., Franz, C. E., Lyons, M. J., Neale, M. C., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23502 · Cited by 58
Sudre, G., Choudhuri, S., Székely, E., Bonner, T., Goduni, E., Sharp, W., & Shaw, P. (2017) · JAMA psychiatry · doi:10.1001/jamapsychiatry.2016.3072 · Cited by 54
Bas‐Hoogendam, J. M., Groenewold, N. A., Aghajani, M., Freitag, G. F., Harrewijn, A., Hilbert, K., Jahanshad, N., Thomopoulos, S. I., Thompson, P. M., Veltman, D. J., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25100 · Cited by 57
Self-citationAdhikari, B. M., Jahanshad, N., Shukla, D., Glahn, D. C., Blangero, J., Fox, P. T., Reynolds, R. C., Cox, R. W., Fieremans, E., Veraart, J., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24331 · Cited by 52
Self-citationMa, D., Popuri, K., Bhalla, M., Sangha, O., Lu, D., Cao, J., Jacova, C., Wang, L., Beg, M. F., & Initiative, A. D. N. (2018) · Human Brain Mapping · doi:10.1002/hbm.24463 · Cited by 53
Convergent Evidence for Predispositional Effects of Brain Gray Matter Volume on Alcohol Consumption
Baranger, D. A. A., Demers, C. H., Elsayed, N. M., Knodt, A. R., Radtke, S. R., Desmarais, A., Few, L. R., Arpana Agrawal, A., Heath, A. C., Barch, D. M., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.08.029 · Cited by 50
Self-citationGrinberg, F., Maximov, I. I., Farrher, E., Neuner, I., Amort, L., Thönneßen, H., Oberwelland, E., Konrad, K., & Shah, N. J. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.033 · Cited by 52
Jahanshad, N., & Thompson, P. M. (2016) · Journal of Neuroscience Research · doi:10.1002/jnr.23919 · Cited by 55
Self-citationWang, N., Anderson, R. J., Ashbrook, D. G., Gopalakrishnan, V., Park, Y., Priebe, C. E., Qi, Y. P., Laoprasert, R., Vogelstein, J. T., Williams, R. W., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117274 · Cited by 47
Foley, S. F., Bracher‐Smith, M., Tansey, K. E., Harrison, J. R., Parker, G. D., & Caseras, X. (2018) · The British Journal of Psychiatry · doi:10.1192/bjp.2018.101 · Cited by 46
Role of physical and mental training in brain network configuration
Foster, P. P. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2015.00117 · Cited by 46
Reproducibility of tract‐based white matter microstructural measures using the ENIGMA ‐ DTI protocol
Acheson, A., Wijtenburg, S. A., Rowland, L. M., Winkler, A., Mathias, C. W., Hong, L. E., Jahanshad, N., Patel, B., Thompson, P. M., McGuire, S. A., et al. (2017) · Brain and Behavior · doi:10.1002/brb3.615 · Cited by 43
Self-citationCampos, L., Arokiaraj, C. M., Chuapoco, M. R., Chen, X., Goeden, N., Gradinaru, V., & Fox, A. S. (2023) · Current Research in Neurobiology · doi:10.1016/j.crneur.2023.100086 · Cited by 42
Balanced translocation linked to psychiatric disorder, glutamate, and cortical structure/function
Thomson, P. A., Duff, B. J., Blackwood, D., Romaniuk, L., Watson, A., Whalley, H. C., Li, X., Dauvermann, M. R., Moorhead, T. W. J., Bois, C., et al. (2016) · Schizophrenia · doi:10.1038/npjschz.2016.24 · Cited by 41
Self-citationA comprehensive tractography study of patients with bipolar disorder and their unaffected siblings
Sprooten, E., Barrett, J., McKay, D., Knowles, E. E. M., Mathias, S. R., Winkler, A. M., Brumbaugh, M. S., Landau, S., Cyr, L., Kochunov, P. V., et al. (2016) · Human Brain Mapping · doi:10.1002/hbm.23253 · Cited by 39
Self-citationEpigenetic Age Acceleration Assessed with Human White-Matter Images
Hodgson, K., Carless, M. A., Kulkarni, H. R., Curran, J. E., Sprooten, E., Knowles, E. E. M., Mathias, S. R., Göring, H. H. H., Yao, N., Olvera, R. L., et al. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0177-17.2017 · Cited by 37
Self-citationDenoising scanner effects from multimodal MRI data using linked independent component analysis
Li, H., Smith, S. M., Gruber, S. A., Lukas, S. E., Silveri, M. M., Hill, K. P., Killgore, W. D. S., & Nickerson, L. D. H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116388 · Cited by 41
Whole mouse brain connectomics
Johnson, G. A., Wang, N., Anderson, R. J., Chen, M., Cofer, G. P., Gee, J. C., Pratson, F., Tustison, N. J., & WHITE, L. E. (2018) · The Journal of Comparative Neurology · doi:10.1002/cne.24560 · Cited by 36
Phenotype‐ and genotype‐specific structural alterations in spasmodic dysphonia
Bianchi, S., Battistella, G., Huddleston, H. P., Scharf, R. J., Fleysher, L., Rumbach, A. F., Frucht, S. J., Blitzer, A., Ozelius, L. J., & Simonyan, K. (2017) · Movement Disorders · doi:10.1002/mds.26920 · Cited by 38
Maximov, I. I., van der Meer, D., de Lange, A. G., Kaufmann, T., Shadrin, A. A., Frei, O., Wolfers, T., & Westlye, L. T. (2021) · Human Brain Mapping · doi:10.1002/hbm.25424 · Cited by 34
Exposure to prenatal maternal distress and infant white matter neurodevelopment
Demers, C. H., Bagonis, M., Al‐Ali, K., Garcia, S. E., Styner, M. A., Gilmore, J. H., Hoffman, M. C., Hankin, B. L., & Davis, E. P. (2021) · Development and Psychopathology · doi:10.1017/s0954579421000742 · Cited by 38
Genetic and Environmental Variation in Continuous Phenotypes in the ABCD Study®
MAES, H. H. M., Lapato, D. M., Schmitt, J. E., Luciana, M. M., Banich, M. T., Bjork, J. M., Hewitt, J. K., Madden, P. A. F., Heath, A. C., Barch, D. M., et al. (2022) · Behavior Genetics · doi:10.1007/s10519-022-10123-w · Cited by 44
Fast and powerful heritability inference for family-based neuroimaging studies
Ganjgahi, H., Winkler, A. M., Glahn, D. C., Blangero, J., Kochunov, P. V., & Nichols, T. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.005 · Cited by 35
Self-citationKochunov, P., Thompson, P. M., Winkler, A. M., Morrissey, M., Fu, M., Coyle, T. R., Du, X. M., Muellerklein, F., Savransky, A., Gaudiot, C., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.050 · Cited by 33
Self-citationAlloza, C., Cox, S. R., Blesa, M., Redmond, P. H., Whalley, H. C., Ritchie, S. J., Maniega, S. M., Hernández, M. D. C. V., Tucker–Drob, E. M., Lawrie, S. M., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.075 · Cited by 34
Self-citationKoshiyama, D., Miura, K., Nemoto, K., Okada, N., Matsumoto, J., Fukunaga, M., & Hashimoto, R. (2020) · Human Brain Mapping · doi:10.1002/hbm.25040 · Cited by 34
Zhao, L., Matloff, W. J., Shi, Y., Cabeen, R. P., & Toga, A. W. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.11.002 · Cited by 32
Fiberprint: A subject fingerprint based on sparse code pooling for white matter fiber analysis
Kumar, K., Desrosiers, C., Kaleem Siddiqi, A., Olivier Colliot, A., & Toews, M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.083 · Cited by 37
Bray, S., Krongold, M., Cooper, C., & Lebel, C. A. (2015) · eNeuro · doi:10.1523/eneuro.0003-15.2015 · Cited by 34
Multi-modal brain fingerprinting: A manifold approximation based framework
Kumar, K., Toews, M., Chauvin, L., Olivier Colliot, A., & Desrosiers, C. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.006 · Cited by 35
Du, X. M., Choa, F., Chiappelli, J., Wisner, K., Wittenberg, G. F., Adhikari, B. M., Bruce, H. A., Rowland, L. M., Kochunov, P. V., & Hong, L. E. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.06.007 · Cited by 31
Self-citationThe Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology
Ge, T., Chen, C., Doyle, A. E., Vettermann, R., Tuominen, L. J., Holt, D. J., Sabuncu, M. R., & Smoller, J. W. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy216 · Cited by 30
Imaging of depressive disorders
Goodwin, G. M., & Browning, M. D. (2020) · doi:10.1093/med/9780198713005.003.0076 · Cited by 29
Hawco, C. S., Voineskos, A. N., Radhu, N., Rotenberg, D. J., Ameis, S. H., Backhouse, F. A., Semeralul, M. O., & Daskalakis, Z. J. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9657-8 · Cited by 28
White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA Epilepsy studyPreprint
Hatton, S. N., Huynh, K. H., Bonilha, L., Abela, E., Alhusaini, S., Altmann, A., Alvim, M. K. M., Balachandra, A. R., Bartolini, E., Bender, B., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.19.883405 · Cited by 28
Self-citationSystematic Bias of Machine Learning Regression Models and Correction
Lee, H., & Chen, S. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3552368 · Cited by 27
Mallas, E., Carletti, F., Chaddock, C. A., Woolley, J., Picchioni, M., Shergill, S. S., Kane, F., Allin, M. P. G., Barker, G. J., & Prata, D. P. (2016) · PeerJ · doi:10.7717/peerj.1570 · Cited by 27
Reproducibility of quantitative structural and physiological MRI measurements
McGuire, S., Wijtenburg, S. A., Sherman, P. M., Rowland, L. M., Ryan, M. C., Sladky, J. H., & Kochunov, P. V. (2017) · Brain and Behavior · doi:10.1002/brb3.759 · Cited by 26
Self-citationPhillips, O. R., Onopa, A., Hsu, V., Ollila, H. M., Hillary, R. P., Hallmayer, J. F., Gotlib, I. H., Taylor, J., Mackey, L. W., & Singh, M. K. (2018) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2018.09.425 · Cited by 27
Bathelt, J., Astle, D. E., Barnes, J., Raymond, F. L., & Baker, K. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.07.016 · Cited by 25
Kochunov, P., Patel, B., Ganjgahi, H., Donohue, B., Ryan, M. C., Hong, L. E., Chen, X., Adhikari, B. M., Jahanshad, N., Thompson, P. M., et al. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00016 · Cited by 26
Self-citationGenetic influences on cortical myelination in the human brain
Liu, S., Li, A., Zhu, M., Li, J., & Liu, B. (2018) · Genes Brain & Behavior · doi:10.1111/gbb.12537 · Cited by 26
Churchill, N. W., Hutchison, M. G., Graham, S. J., & Schweizer, T. A. (2020) · Scientific Reports · doi:10.1038/s41598-020-58073-9 · Cited by 26
White Matter Integrity in High-Altitude Pilots Exposed to Hypobaria
McGuire, S., Boone, G. R. E., Sherman, P. M., Tate, D. F., Wood, J., Patel, B., Eskandar, G., Wijtenburg, S. A., Rowland, L. M., Clarke, G. D., et al. (2016) · Aerospace Medicine and Human Performance · doi:10.3357/amhp.4585.2016 · Cited by 24
Self-citationMa, R. E., Akçakaya, M., Moeller, S., Auerbach, E. J., Uǧurbil, K., & de Moortele, P. V. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116861 · Cited by 24
Self-citationGenetic imaging consortium for addiction medicine
Mackey, S., Kan, K., Chaarani, B., Alia‐Klein, N., Batalla, A., Brooks, S. J., Cousijn, J., Dagher, A., de Ruiter, M. B., Desrivières, S., et al. (2015) · Progress in brain research · doi:10.1016/bs.pbr.2015.07.026 · Cited by 24
Self-citationWhite matter pathways mediate parental effects on children’s reading precursors
Vandermosten, M., Cuynen, L., Vanderauwera, J., Wouters, J. M., & Ghesquière, P. (2017) · Brain and Language · doi:10.1016/j.bandl.2017.05.002 · Cited by 24
Nolvi, S., Tuulari, J. J., Lavonius, T. I., Scheinin, N. M., Lehtola, S. J., Lavonius, M., Merisaari, H., Saunavaara, J. P., Korja, R., Kataja, E., et al. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa081 · Cited by 27
Heritability of complex white matter diffusion traits assessed in a population isolate
Kochunov, P., Fu, M., Nugent, K. L., Wright, S. N., Du, X. M., Muellerklein, F., Morrissey, M., Eskandar, G., Shukla, D. K., Jahanshad, N., et al. (2015) · Human Brain Mapping · doi:10.1002/hbm.23047 · Cited by 26
Self-citationIntergenerational Neuroimaging of Human Brain Circuitry
Ho, T. C., Sanders, S., Gotlib, I. H., & Hoeft, F. (2016) · Trends in Neurosciences · doi:10.1016/j.tins.2016.08.003 · Cited by 21
Evidence for genetic correlation between human cerebral white matter microstructure and inflammation
Rodrigue, A., Knowles, E. E. M., Mollon, J., Mathias, S. R., Koenis, M. M. G., Peralta, J. M., Leandro, A. C., Fox, P. T., Sprooten, E., Kochunov, P., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24694 · Cited by 21
Self-citationAbbas Babajani-feremi, A. (2017) · Brain Topography · doi:10.1007/s10548-017-0550-6 · Cited by 22
Precision medicine for psychopharmacology: a general introduction
Shin, C., Han, C., Pae, C., & Patkar, A. A. (2016) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2016.1182022 · Cited by 21
Genetic influence is linked to cortical morphology in category-selective areas of visual cortex
Abbasi, N., Duncan, J., & Rajimehr, R. (2020) · Nature Communications · doi:10.1038/s41467-020-14610-8 · Cited by 20
“RADIOTRANSCRIPTOMICS”: A synergy of imaging and transcriptomics in clinical assessment
Katrib, A., Hsu, W. W. Y., Bui, A. A. T., & Xing, Y. (2016) · Quantitative Biology · doi:10.1007/s40484-016-0061-6 · Cited by 21
Jahanshad, N., Ganjgahi, H., Bralten, J., den Braber, A., Faskowitz, J., Knodt, A. R., Lemaître, H., Nir, T. M., Patel, B., Richie, S., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/107987 · Cited by 21
Self-citationLuo, Z., Adluru, N., Dean, D., Alexander, A. L., & Goldsmith, H. H. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02393-7 · Cited by 17
Sudre, G. P., Bouyssi-Kobar, M., Norman, L. J., Sharp, W. S., Choudhury, S., & Shaw, P. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.06.007 · Cited by 18
Genetics of structural connectivity and information processing in the brain
Giddaluru, S., Espeseth, T., Salami, A., Westlye, L. T., Lundquist, A., Christoforou, A., Cichon, S., Adolfsson, R., Steen, V. M., Reinvang, I., et al. (2016) · Brain Structure and Function · doi:10.1007/s00429-016-1194-0 · Cited by 19
Hemispheric Asymmetry in the Genetic Overlap between Schizophrenia and White Matter Microstructure
Zhang, Y., Liu, M., Wang, S., Zhang, W., Dong, H., Qian, Q., Wu, Y., Wu, Q., Xu, J., Zhai, Y., et al. (2025) · Cyborg and Bionic Systems · doi:10.34133/cbsystems.0451 · Cited by 18
Hatton, S. N., Panizzon, M. S., Vuoksimaa, E., Hagler, D. J., Fennema‐Notestine, C., Rinker, D. A., Eyler, L. T., Franz, C. E., Lyons, M. J., Neale, M. C., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24002 · Cited by 15
Metadata
- Authors
- Kochunov, P., Jahanshad, N., Marcus, D., Winkler, A., Sprooten, E., Nichols, T. E., Wright, S. N., Hong, L. E., Patel, B., Behrens, T., Jbabdi, S., Andersson, J., Lenglet, C., Yacoub, E., Moeller, S., Auerbach, E., Ugurbil, K., Sotiropoulos, S. N., Brouwer, R. M., Landman, B., Lemaitre, H., den Braber, A., Zwiers, M. P., Ritchie, S., van Hulzen, K., Almasy, L., Curran, J., deZubicaray, G. I., Duggirala, R., Fox, P., Martin, N. G., McMahon, K. L., Mitchell, B., Olvera, R. L., Peterson, C., Starr, J., Sussmann, J., Wardlaw, J., Wright, M., Boomsma, D. I., Kahn, R., de Geus, E. J. C., Williamson, D. E., Hariri, A., van 't Ent, D., Bastin, M. E., McIntosh, A., Deary, I. J., Hulshoff pol, H. E., Blangero, J., Thompson, P. M., Glahn, D. C., & Van Essen, D. C.
- Affiliations
- University of Maryland, Baltimore (US)
- University of Southern California (US)
- Washington University in St. Louis (US)
- University of Oxford (GB)
- Hartford Hospital (US)
- University of Warwick (GB)
- University of Minnesota (US)
- Utrecht University (NL)
- Vanderbilt University (US)
- Radboud University Nijmegen (NL)
- University of Edinburgh (GB)
- Texas Biomedical Research Institute (US)
- The University of Texas at San Antonio Health Science Center (US)
- QIMR Berghofer Medical Research Institute (AU)
- The University of Queensland (AU)
- Vrije Universiteit Amsterdam (NL)
- Duke University (US)
- Corresponding author
- Kochunov, Peter
- ORCID
- Kochunov, Peter
- Jahanshad, Neda
- Winkler, Anderson
- Sprooten, Emma
- Nichols, Thomas E.
- Hong, L. Elliot
- Patel, Binish
- Behrens, Timothy
- Andersson, Jesper
- Lenglet, Christophe
- Yacoub, Essa
- Moeller, Steen
- Sotiropoulos, Stamatios N.
- Brouwer, Rachel M.
- Landman, Bennett
- Zwiers, Marcel P.
- Ritchie, Stuart
- Almasy, Laura
- Curran, Joanne
- Fox, Peter
- Martin, Nicholas G.
- McMahon, Katie L.
- Mitchell, Braxton
- Olvera, Rene L.
- Starr, John
- Wardlaw, Joanna
- Boomsma, Dorret I.
- Williamson, Douglas E.
- Hariri, Ahmad
- Bastin, Mark E.
- McIntosh, Andrew
- Deary, Ian J.
- Blangero, John
- Thompson, Paul M.
- Glahn, David C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 111
- Pages
- 300-311
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4387079
- OpenAlex
- W1985450416
- Cited by
- 215
- References
- 63
- Citations by year
- 2026: 7 · 2025: 15 · 2024: 21 · 2023: 9 · 2022: 8 · 2021: 19 · 2020: 29 · 2019: 17 · 2018: 33 · 2017: 24 · 2016: 21 · 2015: 12
- FWCI
- 24.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- ORBi (University of Liège) (submittedVersion, other-oa)
- Pure Amsterdam UMC (submittedVersion)
- VU Research Portal (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- NIH R01 (EB008432, EB008281, EB007813)
- NIH (087727/Z/08/Z, U54 EB020403)
- Biotechnology Research Center (P41 EB0 15894)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- heritability, fractional anisotropy, white matter microstructure, diffusion tensor imaging, monozygotic and dizygotic twins, siblings, white matter tracts, Human Connectome Project, imaging genetics, gene discovery
- MeSH terms
- Adult, Female, Humans, Male, Nerve Net, Registries, Cohort Studies, Anisotropy, Genetic Phenomena, Young Adult, Diffusion Tensor Imaging, Connectome, White Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
