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Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome.

Biological psychiatry. Cognitive neuroscience and neuroimaging

Jalbrzikowski M, Ahmed KH, Patel A, Jonas R, Kushan L, Chow C, Bearden CE.
PMID: 28367513
Biol Psychiatry Cogn Neurosci Neuroimaging. 2017 Jan;2(1):53-65. doi: 10.1016/j.bpsc.2016.06.007.

BACKGROUND: 22q11.2 Microdeletion syndrome (22q11DS) is associated with elevated rates of autism spectrum disorders (ASDs), although the diagnosis is controversial. In order to determine whether there is a biological substrate of ASD in 22q11DS, we examined neurocognitive and structural...

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Jalbrzikowski M, Ahmed KH, Patel A, et al. Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017;2(1):53-65doi: 10.1016/j.bpsc.2016.06.007.
Jalbrzikowski, M., Ahmed, K. H., Patel, A., Jonas, R., Kushan, L., Chow, C., & Bearden, C. E. (2017). Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome. Biological psychiatry. Cognitive neuroscience and neuroimaging, 2(1), 53-65. https://doi.org/10.1016/j.bpsc.2016.06.007
Jalbrzikowski, Maria, et al. "Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome." Biological psychiatry. Cognitive neuroscience and neuroimaging vol. 2,1 (2017): 53-65. doi: https://doi.org/10.1016/j.bpsc.2016.06.007
Jalbrzikowski M, Ahmed KH, Patel A, Jonas R, Kushan L, Chow C, Bearden CE. Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017 Jan;2(1):53-65. doi: 10.1016/j.bpsc.2016.06.007. PMID: 28367513; PMCID: PMC5373800.
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DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30.

Proceedings. IEEE International Symposium on Biomedical Imaging

Dennis EL, Jahanshad N, Toga AW, McMahon KL, de Zubicaray GI, Hickie I, Wright MJ, Thompson PM.
PMID: 24827471
Proc IEEE Int Symp Biomed Imaging. 2013;624-627. doi: 10.1109/ISBI.2013.6556552.

The 'rich club' coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how...

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Dennis EL, Jahanshad N, Toga AW, et al. DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30. Proc IEEE Int Symp Biomed Imaging. 2013;624-627doi: 10.1109/ISBI.2013.6556552.
Dennis, E. L., Jahanshad, N., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., Hickie, I., Wright, M. J., & Thompson, P. M. (2013). DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30. Proceedings. IEEE International Symposium on Biomedical Imaging, 624-627. https://doi.org/10.1109/ISBI.2013.6556552
Dennis, Emily L, et al. "DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2013): 624-627. doi: https://doi.org/10.1109/ISBI.2013.6556552
Dennis EL, Jahanshad N, Toga AW, McMahon KL, de Zubicaray GI, Hickie I, Wright MJ, Thompson PM. DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30. Proc IEEE Int Symp Biomed Imaging. 2013;624-627. doi: 10.1109/ISBI.2013.6556552. PMID: 24827471; PMCID: PMC4017916.
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Reprint of: Mapping connectivity in the developing brain.

International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience

Dennis EL, Thompson PM.
PMID: 24295552
Int J Dev Neurosci. 2014 Feb;32:41-57. doi: 10.1016/j.ijdevneu.2013.11.005. Epub 2013 Dec 02.

Recently, there has been a wealth of research into structural and functional brain connectivity, and how they change over development. While we are far from a complete understanding, these studies have yielded important insights into human brain development. There...

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Dennis EL, Thompson PM. Reprint of: Mapping connectivity in the developing brain. Int J Dev Neurosci. 2013;32:41-57doi: 10.1016/j.ijdevneu.2013.11.005.
Dennis, E. L., & Thompson, P. M. (2014). Reprint of: Mapping connectivity in the developing brain. International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, 3241-57. https://doi.org/10.1016/j.ijdevneu.2013.11.005
Dennis, Emily L, and Thompson, Paul M. "Reprint of: Mapping connectivity in the developing brain." International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience vol. 32 (2014): 41-57. doi: https://doi.org/10.1016/j.ijdevneu.2013.11.005
Dennis EL, Thompson PM. Reprint of: Mapping connectivity in the developing brain. Int J Dev Neurosci. 2014 Feb;32:41-57. doi: 10.1016/j.ijdevneu.2013.11.005. Epub 2013 Dec 02. PMID: 24295552; PMCID: PMC4442620.
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Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Molecular psychiatry

Han LKM, Dinga R, Hahn T, Ching CRK, Eyler LT, Aftanas L, Aghajani M, Aleman A, Baune BT, Berger K, Brak I, Filho GB, Carballedo A, Connolly CG, Couvy-Duchesne B, Cullen KR, Dannlowski U, Davey CG, Dima D, Duran FLS, Enneking V, Filimonova E, Frenzel S, Frodl T, Fu CHY, Godlewska BR, Gotlib IH, Grabe HJ, Groenewold NA, Grotegerd D, Gruber O, Hall GB, Harrison BJ, Hatton SN, Hermesdorf M, Hickie IB, Ho TC, Hosten N, Jansen A, Kähler C, Kircher T, Klimes-Dougan B, Krämer B, Krug A, Lagopoulos J, Leenings R, MacMaster FP, MacQueen G, McIntosh A, McLellan Q, McMahon KL, Medland SE, Mueller BA, Mwangi B, Osipov E, Portella MJ, Pozzi E, Reneman L, Repple J, Rosa PGP, Sacchet MD, Sämann PG, Schnell K, Schrantee A, Simulionyte E, Soares JC, Sommer J, Stein DJ, Steinsträter O, Strike LT, Thomopoulos SI, van Tol MJ, Veer IM, Vermeiren RRJM, Walter H, van der Wee NJA, van der Werff SJA, Whalley H, Winter NR, Wittfeld K, Wright MJ, Wu MJ, Völzke H, Yang TT, Zannias V, de Zubicaray GI, Zunta-Soares GB, Abé C, Alda M, Andreassen OA, Bøen E, Bonnin CM, Canales-Rodriguez EJ, Cannon D, Caseras X, Chaim-Avancini TM, Elvsåshagen T, Favre P, Foley SF, Fullerton JM, Goikolea JM, Haarman BCM, Hajek T, Henry C, Houenou J, Howells FM, Ingvar M, Kuplicki R, Lafer B, Landén M, Machado-Vieira R, Malt UF, McDonald C, Mitchell PB, Nabulsi L, Otaduy MCG, Overs BJ, Polosan M, Pomarol-Clotet E, Radua J, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Savitz J, Schene AH, Schofield PR, Serpa MH, Sim K, Soeiro-de-Souza MG, Sutherland AN, Temmingh HS, Timmons GM, Uhlmann A, Vieta E, Wolf DH, Zanetti MV, Jahanshad N, Thompson PM, Veltman DJ, Penninx BWJH, Marquand AF, Cole JH, Schmaal L.
PMID: 32424236
Mol Psychiatry. 2021 Sep;26(9):5124-5139. doi: 10.1038/s41380-020-0754-0. Epub 2020 May 18.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large...

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Han LKM, Dinga R, Hahn T, et al. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Mol Psychiatry. 2020;26(9):5124-5139doi: 10.1038/s41380-020-0754-0.
Han, L. K. M., Dinga, R., Hahn, T., Ching, C. R. K., Eyler, L. T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B. T., Berger, K., Brak, I., Filho, G. B., Carballedo, A., Connolly, C. G., Couvy-Duchesne, B., Cullen, K. R., Dannlowski, U., Davey, C. G., Dima, D., Duran, F. L. S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C. H. Y., Godlewska, B. R., Gotlib, I. H., Grabe, H. J., Groenewold, N. A., Grotegerd, D., Gruber, O., Hall, G. B., Harrison, B. J., Hatton, S. N., Hermesdorf, M., Hickie, I. B., Ho, T. C., Hosten, N., Jansen, A., Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F. P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K. L., Medland, S. E., Mueller, B. A., Mwangi, B., Osipov, E., Portella, M. J., Pozzi, E., Reneman, L., Repple, J., Rosa, P. G. P., Sacchet, M. D., Sämann, P. G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J. C., Sommer, J., Stein, D. J., Steinsträter, O., Strike, L. T., Thomopoulos, S. I., van Tol, M. J., Veer, I. M., Vermeiren, R. R. J. M., Walter, H., van der Wee, N. J. A., van der Werff, S. J. A., Whalley, H., Winter, N. R., Wittfeld, K., Wright, M. J., Wu, M. J., Völzke, H., Yang, T. T., Zannias, V., de Zubicaray, G. I., Zunta-Soares, G. B., Abé, C., Alda, M., Andreassen, O. A., Bøen, E., Bonnin, C. M., Canales-Rodriguez, E. J., Cannon, D., Caseras, X., Chaim-Avancini, T. M., Elvsåshagen, T., Favre, P., Foley, S. F., Fullerton, J. M., Goikolea, J. M., Haarman, B. C. M., Hajek, T., Henry, C., Houenou, J., Howells, F. M., Ingvar, M., Kuplicki, R., Lafer, B., Landén, M., Machado-Vieira, R., Malt, U. F., McDonald, C., Mitchell, P. B., Nabulsi, L., Otaduy, M. C. G., Overs, B. J., Polosan, M., Pomarol-Clotet, E., Radua, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarró, S., Satterthwaite, T. D., Savitz, J., Schene, A. H., Schofield, P. R., Serpa, M. H., Sim, K., Soeiro-de-Souza, M. G., Sutherland, A. N., Temmingh, H. S., Timmons, G. M., Uhlmann, A., Vieta, E., Wolf, D. H., Zanetti, M. V., Jahanshad, N., Thompson, P. M., Veltman, D. J., Penninx, B. W. J. H., Marquand, A. F., Cole, J. H., & Schmaal, L. (2021). Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Molecular psychiatry, 26(9), 5124-5139. https://doi.org/10.1038/s41380-020-0754-0
Han, Laura K M, et al. "Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group." Molecular psychiatry vol. 26,9 (2021): 5124-5139. doi: https://doi.org/10.1038/s41380-020-0754-0
Han LKM, Dinga R, Hahn T, Ching CRK, Eyler LT, Aftanas L, Aghajani M, Aleman A, Baune BT, Berger K, Brak I, Filho GB, Carballedo A, Connolly CG, Couvy-Duchesne B, Cullen KR, Dannlowski U, Davey CG, Dima D, Duran FLS, Enneking V, Filimonova E, Frenzel S, Frodl T, Fu CHY, Godlewska BR, Gotlib IH, Grabe HJ, Groenewold NA, Grotegerd D, Gruber O, Hall GB, Harrison BJ, Hatton SN, Hermesdorf M, Hickie IB, Ho TC, Hosten N, Jansen A, Kähler C, Kircher T, Klimes-Dougan B, Krämer B, Krug A, Lagopoulos J, Leenings R, MacMaster FP, MacQueen G, McIntosh A, McLellan Q, McMahon KL, Medland SE, Mueller BA, Mwangi B, Osipov E, Portella MJ, Pozzi E, Reneman L, Repple J, Rosa PGP, Sacchet MD, Sämann PG, Schnell K, Schrantee A, Simulionyte E, Soares JC, Sommer J, Stein DJ, Steinsträter O, Strike LT, Thomopoulos SI, van Tol MJ, Veer IM, Vermeiren RRJM, Walter H, van der Wee NJA, van der Werff SJA, Whalley H, Winter NR, Wittfeld K, Wright MJ, Wu MJ, Völzke H, Yang TT, Zannias V, de Zubicaray GI, Zunta-Soares GB, Abé C, Alda M, Andreassen OA, Bøen E, Bonnin CM, Canales-Rodriguez EJ, Cannon D, Caseras X, Chaim-Avancini TM, Elvsåshagen T, Favre P, Foley SF, Fullerton JM, Goikolea JM, Haarman BCM, Hajek T, Henry C, Houenou J, Howells FM, Ingvar M, Kuplicki R, Lafer B, Landén M, Machado-Vieira R, Malt UF, McDonald C, Mitchell PB, Nabulsi L, Otaduy MCG, Overs BJ, Polosan M, Pomarol-Clotet E, Radua J, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Savitz J, Schene AH, Schofield PR, Serpa MH, Sim K, Soeiro-de-Souza MG, Sutherland AN, Temmingh HS, Timmons GM, Uhlmann A, Vieta E, Wolf DH, Zanetti MV, Jahanshad N, Thompson PM, Veltman DJ, Penninx BWJH, Marquand AF, Cole JH, Schmaal L. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Mol Psychiatry. 2021 Sep;26(9):5124-5139. doi: 10.1038/s41380-020-0754-0. Epub 2020 May 18. PMID: 32424236; PMCID: PMC8589647.
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CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS.

Proceedings. IEEE International Symposium on Biomedical Imaging

Dennis EL, Jahanshad N, Toga AW, Johnson K, McMahon KL, de Zubicaray GI, Martin NG, Hickie IB, Wright MJ, Thompson PM.
PMID: 22903354
Proc IEEE Int Symp Biomed Imaging. 2012;904-908. doi: 10.1109/ISBI.2012.6235695.

Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but...

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Dennis EL, Jahanshad N, Toga AW, et al. CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS. Proc IEEE Int Symp Biomed Imaging. 2012;904-908doi: 10.1109/ISBI.2012.6235695.
Dennis, E. L., Jahanshad, N., Toga, A. W., Johnson, K., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Hickie, I. B., Wright, M. J., & Thompson, P. M. (2012). CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS. Proceedings. IEEE International Symposium on Biomedical Imaging, 904-908. https://doi.org/10.1109/ISBI.2012.6235695
Dennis, Emily L, et al. "CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2012): 904-908. doi: https://doi.org/10.1109/ISBI.2012.6235695
Dennis EL, Jahanshad N, Toga AW, Johnson K, McMahon KL, de Zubicaray GI, Martin NG, Hickie IB, Wright MJ, Thompson PM. CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS. Proc IEEE Int Symp Biomed Imaging. 2012;904-908. doi: 10.1109/ISBI.2012.6235695. PMID: 22903354; PMCID: PMC3420974.
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What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group.

Human brain mapping

Ching CRK, Hibar DP, Gurholt TP, Nunes A, Thomopoulos SI, Abé C, Agartz I, Brouwer RM, Cannon DM, de Zwarte SMC, Eyler LT, Favre P, Hajek T, Haukvik UK, Houenou J, Landén M, Lett TA, McDonald C, Nabulsi L, Patel Y, Pauling ME, Paus T, Radua J, Soeiro-de-Souza MG, Tronchin G, van Haren NEM, Vieta E, Walter H, Zeng LL, Alda M, Almeida J, Alnaes D, Alonso-Lana S, Altimus C, Bauer M, Baune BT, Bearden CE, Bellani M, Benedetti F, Berk M, Bilderbeck AC, Blumberg HP, Bøen E, Bollettini I, Del Mar Bonnin C, Brambilla P, Canales-Rodríguez EJ, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, Dima D, Duchesnay É, Elvsåshagen T, Fears SC, Frangou S, Fullerton JM, Glahn DC, Goikolea JM, Green MJ, Grotegerd D, Gruber O, Haarman BCM, Henry C, Howells FM, Ives-Deliperi V, Jansen A, Kircher TTJ, Knöchel C, Kramer B, Lafer B, López-Jaramillo C, Machado-Vieira R, MacIntosh BJ, Melloni EMT, Mitchell PB, Nenadic I, Nery F, Nugent AC, Oertel V, Ophoff RA, Ota M, Overs BJ, Pham DL, Phillips ML, Pineda-Zapata JA, Poletti S, Polosan M, Pomarol-Clotet E, Pouchon A, Quidé Y, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Schene AH, Sim K, Soares JC, Stäblein M, Stein DJ, Tamnes CK, Thomaidis GV, Upegui CV, Veltman DJ, Wessa M, Westlye LT, Whalley HC, Wolf DH, Wu MJ, Yatham LN, Zarate CA, Thompson PM, Andreassen OA.
PMID: 32725849
Hum Brain Mapp. 2022 Jan;43(1):56-82. doi: 10.1002/hbm.25098. Epub 2020 Jul 29.

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The...

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Ching CRK, Hibar DP, Gurholt TP, et al. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group. Hum Brain Mapp. 2020;43(1):56-82doi: 10.1002/hbm.25098.
Ching, C. R. K., Hibar, D. P., Gurholt, T. P., Nunes, A., Thomopoulos, S. I., Abé, C., Agartz, I., Brouwer, R. M., Cannon, D. M., de Zwarte, S. M. C., Eyler, L. T., Favre, P., Hajek, T., Haukvik, U. K., Houenou, J., Landén, M., Lett, T. A., McDonald, C., Nabulsi, L., Patel, Y., Pauling, M. E., Paus, T., Radua, J., Soeiro-de-Souza, M. G., Tronchin, G., van Haren, N. E. M., Vieta, E., Walter, H., Zeng, L. L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M., Baune, B. T., Bearden, C. E., Bellani, M., Benedetti, F., Berk, M., Bilderbeck, A. C., Blumberg, H. P., Bøen, E., Bollettini, I., Del Mar Bonnin, C., Brambilla, P., Canales-Rodríguez, E. J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A. M., Dima, D., Duchesnay, �. �., Elvsåshagen, T., Fears, S. C., Frangou, S., Fullerton, J. M., Glahn, D. C., Goikolea, J. M., Green, M. J., Grotegerd, D., Gruber, O., Haarman, B. C. M., Henry, C., Howells, F. M., Ives-Deliperi, V., Jansen, A., Kircher, T. T. J., Knöchel, C., Kramer, B., Lafer, B., López-Jaramillo, C., Machado-Vieira, R., MacIntosh, B. J., Melloni, E. M. T., Mitchell, P. B., Nenadic, I., Nery, F., Nugent, A. C., Oertel, V., Ophoff, R. A., Ota, M., Overs, B. J., Pham, D. L., Phillips, M. L., Pineda-Zapata, J. A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quidé, Y., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarró, S., Satterthwaite, T. D., Schene, A. H., Sim, K., Soares, J. C., Stäblein, M., Stein, D. J., Tamnes, C. K., Thomaidis, G. V., Upegui, C. V., Veltman, D. J., Wessa, M., Westlye, L. T., Whalley, H. C., Wolf, D. H., Wu, M. J., Yatham, L. N., Zarate, C. A., Thompson, P. M., Andreassen, O. A. (2022). What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group. Human brain mapping, 43(1), 56-82. https://doi.org/10.1002/hbm.25098
Ching, Christopher R K, et al. "What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group." Human brain mapping vol. 43,1 (2022): 56-82. doi: https://doi.org/10.1002/hbm.25098
Ching CRK, Hibar DP, Gurholt TP, Nunes A, Thomopoulos SI, Abé C, Agartz I, Brouwer RM, Cannon DM, de Zwarte SMC, Eyler LT, Favre P, Hajek T, Haukvik UK, Houenou J, Landén M, Lett TA, McDonald C, Nabulsi L, Patel Y, Pauling ME, Paus T, Radua J, Soeiro-de-Souza MG, Tronchin G, van Haren NEM, Vieta E, Walter H, Zeng LL, Alda M, Almeida J, Alnaes D, Alonso-Lana S, Altimus C, Bauer M, Baune BT, Bearden CE, Bellani M, Benedetti F, Berk M, Bilderbeck AC, Blumberg HP, Bøen E, Bollettini I, Del Mar Bonnin C, Brambilla P, Canales-Rodríguez EJ, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, Dima D, Duchesnay É, Elvsåshagen T, Fears SC, Frangou S, Fullerton JM, Glahn DC, Goikolea JM, Green MJ, Grotegerd D, Gruber O, Haarman BCM, Henry C, Howells FM, Ives-Deliperi V, Jansen A, Kircher TTJ, Knöchel C, Kramer B, Lafer B, López-Jaramillo C, Machado-Vieira R, MacIntosh BJ, Melloni EMT, Mitchell PB, Nenadic I, Nery F, Nugent AC, Oertel V, Ophoff RA, Ota M, Overs BJ, Pham DL, Phillips ML, Pineda-Zapata JA, Poletti S, Polosan M, Pomarol-Clotet E, Pouchon A, Quidé Y, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Schene AH, Sim K, Soares JC, Stäblein M, Stein DJ, Tamnes CK, Thomaidis GV, Upegui CV, Veltman DJ, Wessa M, Westlye LT, Whalley HC, Wolf DH, Wu MJ, Yatham LN, Zarate CA, Thompson PM, Andreassen OA. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group. Hum Brain Mapp. 2022 Jan;43(1):56-82. doi: 10.1002/hbm.25098. Epub 2020 Jul 29. PMID: 32725849; PMCID: PMC8675426.
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Greater male than female variability in regional brain structure across the lifespan.

Human brain mapping

Wierenga LM, Doucet GE, Dima D, Agartz I, Aghajani M, Akudjedu TN, Albajes-Eizagirre A, Alnaes D, Alpert KI, Andreassen OA, Anticevic A, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur-Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, den Braber A, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Calhoun VD, Canales-Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Chaim-Avancini TM, Ching CR, Clark VP, Conrod PJ, Conzelmann A, Crivello F, Davey CG, Dickie EW, Ehrlich S, Van't Ent D, Fisher SE, Fouche JP, Franke B, Fuentes-Claramonte P, de Geus EJ, Di Giorgio A, Glahn DC, Gotlib IH, Grabe HJ, Gruber O, Gruner P, Gur RE, Gur RC, Gurholt TP, de Haan L, Haatveit B, Harrison BJ, Hartman CA, Hatton SN, Heslenfeld DJ, van den Heuvel OA, Hickie IB, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James AC, Jiang J, Jönsson EG, Joska JA, Kalnin AJ, Klein M, Koenders L, Kolskår KK, Krämer B, Kuntsi J, Lagopoulos J, Lazaro L, Lebedeva IS, Lee PH, Lochner C, Machielsen MW, Maingault S, Martin NG, Martínez-Zalacaín I, Mataix-Cols D, Mazoyer B, McDonald BC, McDonald C, McIntosh AM, McMahon KL, McPhilemy G, van der Meer D, Menchón JM, Naaijen J, Nyberg L, Oosterlaan J, Paloyelis Y, Pauli P, Pergola G, Pomarol-Clotet E, Portella MJ, Radua J, Reif A, Richard G, Roffman JL, Rosa PG, Sacchet MD, Sachdev PS, Salvador R, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Sim K, Simmons A, Smoller JW, Sommer IE, Soriano-Mas C, Stein DJ, Strike LT, Szeszko PR, Temmingh HS, Thomopoulos SI, Tomyshev AS, Trollor JN, Uhlmann A, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Wang L, Wang Y, Weber B, Wen W, West JD, Westlye LT, Whalley HC, Williams SC, Wittfeld K, Wolf DH, Wright MJ, Yoncheva YN, Zanetti MV, Ziegler GC, de Zubicaray GI, Thompson PM, Crone EA, Frangou S, Tamnes CK.
PMID: 33044802
Hum Brain Mapp. 2020 Oct 12; doi: 10.1002/hbm.25204. Epub 2020 Oct 12.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability...

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Wierenga LM, Doucet GE, Dima D, et al. Greater male than female variability in regional brain structure across the lifespan. Hum Brain Mapp. 2020;doi: 10.1002/hbm.25204.
Wierenga, L. M., Doucet, G. E., Dima, D., Agartz, I., Aghajani, M., Akudjedu, T. N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K. I., Andreassen, O. A., Anticevic, A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D. I., Borgwardt, S., Bourque, J., den Braber, A., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R. M., Buitelaar, J. K., Busatto, G. F., Calhoun, V. D., Canales-Rodríguez, E. J., Cannon, D. M., Caseras, X., Castellanos, F. X., Chaim-Avancini, T. M., Ching, C. R., Clark, V. P., Conrod, P. J., Conzelmann, A., Crivello, F., Davey, C. G., Dickie, E. W., Ehrlich, S., Van't Ent, D., Fisher, S. E., Fouche, J. P., Franke, B., Fuentes-Claramonte, P., de Geus, E. J., Di Giorgio, A., Glahn, D. C., Gotlib, I. H., Grabe, H. J., Gruber, O., Gruner, P., Gur, R. E., Gur, R. C., Gurholt, T. P., de Haan, L., Haatveit, B., Harrison, B. J., Hartman, C. A., Hatton, S. N., Heslenfeld, D. J., van den Heuvel, O. A., Hickie, I. B., Hoekstra, P. J., Hohmann, S., Holmes, A. J., Hoogman, M., Hosten, N., Howells, F. M., Hulshoff Pol, H. E., Huyser, C., Jahanshad, N., James, A. C., Jiang, J., Jönsson, E. G., Joska, J. A., Kalnin, A. J., Klein, M., Koenders, L., Kolskår, K. K., Krämer, B., Kuntsi, J., Lagopoulos, J., Lazaro, L., Lebedeva, I. S., Lee, P. H., Lochner, C., Machielsen, M. W., Maingault, S., Martin, N. G., Martínez-Zalacaín, I., Mataix-Cols, D., Mazoyer, B., McDonald, B. C., McDonald, C., McIntosh, A. M., McMahon, K. L., McPhilemy, G., van der Meer, D., Menchón, J. M., Naaijen, J., Nyberg, L., Oosterlaan, J., Paloyelis, Y., Pauli, P., Pergola, G., Pomarol-Clotet, E., Portella, M. J., Radua, J., Reif, A., Richard, G., Roffman, J. L., Rosa, P. G., Sacchet, M. D., Sachdev, P. S., Salvador, R., Sarró, S., Satterthwaite, T. D., Saykin, A. J., Serpa, M. H., Sim, K., Simmons, A., Smoller, J. W., Sommer, I. E., Soriano-Mas, C., Stein, D. J., Strike, L. T., Szeszko, P. R., Temmingh, H. S., Thomopoulos, S. I., Tomyshev, A. S., Trollor, J. N., Uhlmann, A., Veer, I. M., Veltman, D. J., Voineskos, A., Völzke, H., Walter, H., Wang, L., Wang, Y., Weber, B., Wen, W., West, J. D., Westlye, L. T., Whalley, H. C., Williams, S. C., Wittfeld, K., Wolf, D. H., Wright, M. J., Yoncheva, Y. N., Zanetti, M. V., Ziegler, G. C., de Zubicaray, G. I., Thompson, P. M., Crone, E. A., Frangou, S., & Tamnes, C. K. (2020). Greater male than female variability in regional brain structure across the lifespan. Human brain mapping, . https://doi.org/10.1002/hbm.25204
Wierenga, Lara M, et al. "Greater male than female variability in regional brain structure across the lifespan." Human brain mapping vol. (2020). doi: https://doi.org/10.1002/hbm.25204
Wierenga LM, Doucet GE, Dima D, Agartz I, Aghajani M, Akudjedu TN, Albajes-Eizagirre A, Alnaes D, Alpert KI, Andreassen OA, Anticevic A, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur-Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, den Braber A, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Calhoun VD, Canales-Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Chaim-Avancini TM, Ching CR, Clark VP, Conrod PJ, Conzelmann A, Crivello F, Davey CG, Dickie EW, Ehrlich S, Van't Ent D, Fisher SE, Fouche JP, Franke B, Fuentes-Claramonte P, de Geus EJ, Di Giorgio A, Glahn DC, Gotlib IH, Grabe HJ, Gruber O, Gruner P, Gur RE, Gur RC, Gurholt TP, de Haan L, Haatveit B, Harrison BJ, Hartman CA, Hatton SN, Heslenfeld DJ, van den Heuvel OA, Hickie IB, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James AC, Jiang J, Jönsson EG, Joska JA, Kalnin AJ, Klein M, Koenders L, Kolskår KK, Krämer B, Kuntsi J, Lagopoulos J, Lazaro L, Lebedeva IS, Lee PH, Lochner C, Machielsen MW, Maingault S, Martin NG, Martínez-Zalacaín I, Mataix-Cols D, Mazoyer B, McDonald BC, McDonald C, McIntosh AM, McMahon KL, McPhilemy G, van der Meer D, Menchón JM, Naaijen J, Nyberg L, Oosterlaan J, Paloyelis Y, Pauli P, Pergola G, Pomarol-Clotet E, Portella MJ, Radua J, Reif A, Richard G, Roffman JL, Rosa PG, Sacchet MD, Sachdev PS, Salvador R, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Sim K, Simmons A, Smoller JW, Sommer IE, Soriano-Mas C, Stein DJ, Strike LT, Szeszko PR, Temmingh HS, Thomopoulos SI, Tomyshev AS, Trollor JN, Uhlmann A, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Wang L, Wang Y, Weber B, Wen W, West JD, Westlye LT, Whalley HC, Williams SC, Wittfeld K, Wolf DH, Wright MJ, Yoncheva YN, Zanetti MV, Ziegler GC, de Zubicaray GI, Thompson PM, Crone EA, Frangou S, Tamnes CK. Greater male than female variability in regional brain structure across the lifespan. Hum Brain Mapp. 2020 Oct 12; doi: 10.1002/hbm.25204. Epub 2020 Oct 12. PMID: 33044802.
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ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research.

Human brain mapping

Kochunov P, Hong LE, Dennis EL, Morey RA, Tate DF, Wilde EA, Logue M, Kelly S, Donohoe G, Favre P, Houenou J, Ching CRK, Holleran L, Andreassen OA, van Velzen LS, Schmaal L, Villalón-Reina JE, Bearden CE, Piras F, Spalletta G, van den Heuvel OA, Veltman DJ, Stein DJ, Ryan MC, Tan Y, van Erp TGM, Turner JA, Haddad L, Nir TM, Glahn DC, Thompson PM, Jahanshad N.
PMID: 32301246
Hum Brain Mapp. 2022 Jan;43(1):194-206. doi: 10.1002/hbm.24998. Epub 2020 Apr 16.

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations....

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Kochunov P, Hong LE, Dennis EL, et al. ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research. Hum Brain Mapp. 2020;43(1):194-206doi: 10.1002/hbm.24998.
Kochunov, P., Hong, L. E., Dennis, E. L., Morey, R. A., Tate, D. F., Wilde, E. A., Logue, M., Kelly, S., Donohoe, G., Favre, P., Houenou, J., Ching, C. R. K., Holleran, L., Andreassen, O. A., van Velzen, L. S., Schmaal, L., Villalón-Reina, J. E., Bearden, C. E., Piras, F., Spalletta, G., van den Heuvel, O. A., Veltman, D. J., Stein, D. J., Ryan, M. C., Tan, Y., van Erp, T. G. M., Turner, J. A., Haddad, L., Nir, T. M., Glahn, D. C., Thompson, P. M., & Jahanshad, N. (2022). ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research. Human brain mapping, 43(1), 194-206. https://doi.org/10.1002/hbm.24998
Kochunov, Peter, et al. "ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research." Human brain mapping vol. 43,1 (2022): 194-206. doi: https://doi.org/10.1002/hbm.24998
Kochunov P, Hong LE, Dennis EL, Morey RA, Tate DF, Wilde EA, Logue M, Kelly S, Donohoe G, Favre P, Houenou J, Ching CRK, Holleran L, Andreassen OA, van Velzen LS, Schmaal L, Villalón-Reina JE, Bearden CE, Piras F, Spalletta G, van den Heuvel OA, Veltman DJ, Stein DJ, Ryan MC, Tan Y, van Erp TGM, Turner JA, Haddad L, Nir TM, Glahn DC, Thompson PM, Jahanshad N. ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research. Hum Brain Mapp. 2022 Jan;43(1):194-206. doi: 10.1002/hbm.24998. Epub 2020 Apr 16. PMID: 32301246; PMCID: PMC8675425.
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In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

Human brain mapping

Haukvik UK, Gurholt TP, Nerland S, Elvsåshagen T, Akudjedu TN, Alda M, Alnaes D, Alonso-Lana S, Bauer J, Baune BT, Benedetti F, Berk M, Bettella F, Bøen E, Bonnín CM, Brambilla P, Canales-Rodríguez EJ, Cannon DM, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, van Erp TGM, Fatjó-Vilas M, Foley SF, Förster K, Fullerton JM, Goikolea JM, Grotegerd D, Gruber O, Haarman BCM, Haatveit B, Hajek T, Hallahan B, Harris M, Hawkins EL, Howells FM, Hülsmann C, Jahanshad N, Jørgensen KN, Kircher T, Krämer B, Krug A, Kuplicki R, Lagerberg TV, Lancaster TM, Lenroot RK, Lonning V, López-Jaramillo C, Malt UF, McDonald C, McIntosh AM, McPhilemy G, van der Meer D, Melle I, Melloni EMT, Mitchell PB, Nabulsi L, Nenadić I, Oertel V, Oldani L, Opel N, Otaduy MCG, Overs BJ, Pineda-Zapata JA, Pomarol-Clotet E, Radua J, Rauer L, Redlich R, Repple J, Rive MM, Roberts G, Ruhe HG, Salminen LE, Salvador R, Sarró S, Savitz J, Schene AH, Sim K, Soeiro-de-Souza MG, Stäblein M, Stein DJ, Stein F, Tamnes CK, Temmingh HS, Thomopoulos SI, Veltman DJ, Vieta E, Waltemate L, Westlye LT, Whalley HC, Sämann PG, Thompson PM, Ching CRK, Andreassen OA, Agartz I.
PMID: 33073925
Hum Brain Mapp. 2022 Jan;43(1):385-398. doi: 10.1002/hbm.25249. Epub 2020 Oct 19.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted...

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Haukvik UK, Gurholt TP, Nerland S, et al. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group. Hum Brain Mapp. 2020;43(1):385-398doi: 10.1002/hbm.25249.
Haukvik, U. K., Gurholt, T. P., Nerland, S., Elvsåshagen, T., Akudjedu, T. N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B. T., Benedetti, F., Berk, M., Bettella, F., Bøen, E., Bonnín, C. M., Brambilla, P., Canales-Rodríguez, E. J., Cannon, D. M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A. M., van Erp, T. G. M., Fatjó-Vilas, M., Foley, S. F., Förster, K., Fullerton, J. M., Goikolea, J. M., Grotegerd, D., Gruber, O., Haarman, B. C. M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E. L., Howells, F. M., Hülsmann, C., Jahanshad, N., Jørgensen, K. N., Kircher, T., Krämer, B., Krug, A., Kuplicki, R., Lagerberg, T. V., Lancaster, T. M., Lenroot, R. K., Lonning, V., López-Jaramillo, C., Malt, U. F., McDonald, C., McIntosh, A. M., McPhilemy, G., van der Meer, D., Melle, I., Melloni, E. M. T., Mitchell, P. B., Nabulsi, L., Nenadić, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M. C. G., Overs, B. J., Pineda-Zapata, J. A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salminen, L. E., Salvador, R., Sarró, S., Savitz, J., Schene, A. H., Sim, K., Soeiro-de-Souza, M. G., Stäblein, M., Stein, D. J., Stein, F., Tamnes, C. K., Temmingh, H. S., Thomopoulos, S. I., Veltman, D. J., Vieta, E., Waltemate, L., Westlye, L. T., Whalley, H. C., Sämann, P. G., Thompson, P. M., Ching, C. R. K., Andreassen, O. A., Agartz, I. (2022). In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group. Human brain mapping, 43(1), 385-398. https://doi.org/10.1002/hbm.25249
Haukvik, Unn K, et al. "In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group." Human brain mapping vol. 43,1 (2022): 385-398. doi: https://doi.org/10.1002/hbm.25249
Haukvik UK, Gurholt TP, Nerland S, Elvsåshagen T, Akudjedu TN, Alda M, Alnaes D, Alonso-Lana S, Bauer J, Baune BT, Benedetti F, Berk M, Bettella F, Bøen E, Bonnín CM, Brambilla P, Canales-Rodríguez EJ, Cannon DM, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, van Erp TGM, Fatjó-Vilas M, Foley SF, Förster K, Fullerton JM, Goikolea JM, Grotegerd D, Gruber O, Haarman BCM, Haatveit B, Hajek T, Hallahan B, Harris M, Hawkins EL, Howells FM, Hülsmann C, Jahanshad N, Jørgensen KN, Kircher T, Krämer B, Krug A, Kuplicki R, Lagerberg TV, Lancaster TM, Lenroot RK, Lonning V, López-Jaramillo C, Malt UF, McDonald C, McIntosh AM, McPhilemy G, van der Meer D, Melle I, Melloni EMT, Mitchell PB, Nabulsi L, Nenadić I, Oertel V, Oldani L, Opel N, Otaduy MCG, Overs BJ, Pineda-Zapata JA, Pomarol-Clotet E, Radua J, Rauer L, Redlich R, Repple J, Rive MM, Roberts G, Ruhe HG, Salminen LE, Salvador R, Sarró S, Savitz J, Schene AH, Sim K, Soeiro-de-Souza MG, Stäblein M, Stein DJ, Stein F, Tamnes CK, Temmingh HS, Thomopoulos SI, Veltman DJ, Vieta E, Waltemate L, Westlye LT, Whalley HC, Sämann PG, Thompson PM, Ching CRK, Andreassen OA, Agartz I. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group. Hum Brain Mapp. 2022 Jan;43(1):385-398. doi: 10.1002/hbm.25249. Epub 2020 Oct 19. PMID: 33073925; PMCID: PMC8675404.
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Insights into multimodal imaging classification of ADHD.

Frontiers in systems neuroscience

Colby JB, Rudie JD, Brown JA, Douglas PK, Cohen MS, Shehzad Z.
PMID: 22912605
Front Syst Neurosci. 2012 Aug 16;6:59. doi: 10.3389/fnsys.2012.00059. eCollection 2012.

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that...

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Colby JB, Rudie JD, Brown JA, et al. Insights into multimodal imaging classification of ADHD. Front Syst Neurosci. 2012;6:59doi: 10.3389/fnsys.2012.00059.
Colby, J. B., Rudie, J. D., Brown, J. A., Douglas, P. K., Cohen, M. S., & Shehzad, Z. (2012). Insights into multimodal imaging classification of ADHD. Frontiers in systems neuroscience, 659. https://doi.org/10.3389/fnsys.2012.00059
Colby, John B, et al. "Insights into multimodal imaging classification of ADHD." Frontiers in systems neuroscience vol. 6 (2012): 59. doi: https://doi.org/10.3389/fnsys.2012.00059
Colby JB, Rudie JD, Brown JA, Douglas PK, Cohen MS, Shehzad Z. Insights into multimodal imaging classification of ADHD. Front Syst Neurosci. 2012 Aug 16;6:59. doi: 10.3389/fnsys.2012.00059. eCollection 2012. PMID: 22912605; PMCID: PMC3419970.
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Altered functional and structural brain network organization in autism.

NeuroImage. Clinical

Rudie JD, Brown JA, Beck-Pancer D, Hernandez LM, Dennis EL, Thompson PM, Bookheimer SY, Dapretto M.
PMID: 24179761
Neuroimage Clin. 2012 Nov 16;2:79-94. doi: 10.1016/j.nicl.2012.11.006. eCollection 2012.

Structural and functional underconnectivity have been reported for multiple brain regions, functional systems, and white matter tracts in individuals with autism spectrum disorders (ASD). Although recent developments in complex network analysis have established that the brain is a modular...

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Rudie JD, Brown JA, Beck-Pancer D, et al. Altered functional and structural brain network organization in autism. Neuroimage Clin. 2012;2:79-94doi: 10.1016/j.nicl.2012.11.006.
Rudie, J. D., Brown, J. A., Beck-Pancer, D., Hernandez, L. M., Dennis, E. L., Thompson, P. M., Bookheimer, S. Y., & Dapretto, M. (2012). Altered functional and structural brain network organization in autism. NeuroImage. Clinical, 279-94. https://doi.org/10.1016/j.nicl.2012.11.006
Rudie, J D, et al. "Altered functional and structural brain network organization in autism." NeuroImage. Clinical vol. 2 (2012): 79-94. doi: https://doi.org/10.1016/j.nicl.2012.11.006
Rudie JD, Brown JA, Beck-Pancer D, Hernandez LM, Dennis EL, Thompson PM, Bookheimer SY, Dapretto M. Altered functional and structural brain network organization in autism. Neuroimage Clin. 2012 Nov 16;2:79-94. doi: 10.1016/j.nicl.2012.11.006. eCollection 2012. PMID: 24179761; PMCID: PMC3777708.
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A Novel Protocol for Directed Differentiation of C9orf72-Associated Human Induced Pluripotent Stem Cells Into Contractile Skeletal Myotubes.

Stem cells translational medicine

Swartz EW, Baek J, Pribadi M, Wojta KJ, Almeida S, Karydas A, Gao FB, Miller BL, Coppola G.
PMID: 27369896
Stem Cells Transl Med. 2016 Nov;5(11):1461-1472. doi: 10.5966/sctm.2015-0340. Epub 2016 Jul 01.

: Induced pluripotent stem cells (iPSCs) offer an unlimited resource of cells to be used for the study of underlying molecular biology of disease, therapeutic drug screening, and transplant-based regenerative medicine. However, methods for the directed differentiation of skeletal...

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Swartz EW, Baek J, Pribadi M, et al. A Novel Protocol for Directed Differentiation of C9orf72-Associated Human Induced Pluripotent Stem Cells Into Contractile Skeletal Myotubes. Stem Cells Transl Med. 2016;5(11):1461-1472doi: 10.5966/sctm.2015-0340.
Swartz, E. W., Baek, J., Pribadi, M., Wojta, K. J., Almeida, S., Karydas, A., Gao, F. B., Miller, B. L., & Coppola, G. (2016). A Novel Protocol for Directed Differentiation of C9orf72-Associated Human Induced Pluripotent Stem Cells Into Contractile Skeletal Myotubes. Stem cells translational medicine, 5(11), 1461-1472. https://doi.org/10.5966/sctm.2015-0340
Swartz, Elliot W, et al. "A Novel Protocol for Directed Differentiation of C9orf72-Associated Human Induced Pluripotent Stem Cells Into Contractile Skeletal Myotubes." Stem cells translational medicine vol. 5,11 (2016): 1461-1472. doi: https://doi.org/10.5966/sctm.2015-0340
Swartz EW, Baek J, Pribadi M, Wojta KJ, Almeida S, Karydas A, Gao FB, Miller BL, Coppola G. A Novel Protocol for Directed Differentiation of C9orf72-Associated Human Induced Pluripotent Stem Cells Into Contractile Skeletal Myotubes. Stem Cells Transl Med. 2016 Nov;5(11):1461-1472. doi: 10.5966/sctm.2015-0340. Epub 2016 Jul 01. PMID: 27369896; PMCID: PMC5070503.
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