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1. Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study

Author: Lisdahl, Krista M, Tapert, Susan, Sher, Kenneth J, Gonzalez, Raul, Nixon, Sara Jo, Ewing, Sarah W Feldstein, Conway, Kevin P, Wallace, Alex, Sullivan, Ryan, Hatcher, Kelah, Kaiver, Christine, Thompson, Wes, Reuter, Chase, Bartsch, Hauke, Wade, Natasha E, Jacobus, Joanna, Albaugh, MD, Allgaier, N, Anokhin, AP, Bagot, K, Baker, FC, Banich, MT, Barch, DM, Baskin-Sommers, A, Breslin, FJ, Brown, SA, Calhoun, V, Casey, BJ, Chaarani, B, Chang, L, Clark, DB, Cloak, C, Constable, RT, Cottler, LB, Dagher, RK, Dapretto, M, Dick, A, Do, EK, Dosenbach, NUF, Dowling, GJ, Fair, DA, Florsheim, P, Foxe, JJ, Freedman, EG, Friedman, NP, Garavan, HP, Gee, DG, Glantz, MD, Glaser, P, Gonzalez, MR, Gray, KM, Grant, S, Haist, F, Hawes, S, Heeringa, SG, Hermosillo, R, Herting, MM, Hettema, JM, Hewitt, JK, Heyser, C, Hoffman, EA, Howlett, KD, Huber, RS, Huestis, MA, Hyde, LW, Iacono, WG, Isaiah, A, Ivanova, MY, James, RS, Jernigan, TL, Karcher, NR, Kuperman, JM, Laird, AR, Larson, CL, LeBlanc, KH, Lopez, MF, Luciana, M, Luna, B, Maes, HH, Marshall, AT, Mason, MJ, McGlade, E, Morris, AS, Mulford, C, Nagel, BJ, Neigh, G, Palmer, CE, Paulus, MP, Pecheva, D, Prouty, D, Potter, A, Puttler, LI, Rajapakse, N, Ross, JM, Sanchez, M, Schirda, C, Schulenberg, J, Sheth, C, Shilling, PD, and Sowell, ER
Subjects: Paediatrics, Biomedical and Clinical Sciences, Alcoholism, Alcohol Use and Health, Underage Drinking, Social Determinants of Health, Women's Health, Clinical Research, Substance Misuse, Basic Behavioral and Social Science, Drug Abuse (NIDA only), Pediatric, Behavioral and Social Science, Mental Health, Prevention, Health Disparities, Neurosciences, Minority Health, Brain Disorders, 2.3 Psychological, social and economic factors, Stroke, Oral and gastrointestinal, Mental health, Cancer, Good Health and Well Being, Adolescent, Adult, Brain, Child, Child, Preschool, Cognition, Humans, Longitudinal Studies, Prospective Studies, Substance-Related Disorders, ABCD study, Alcohol, Cannabis, Nicotine, Caffeine, Externalizing behaviors, Alcohol sipping, Children, ABCD Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Substance Abuse, Biochemistry and cell biology, Pharmacology and pharmaceutical sciences, Epidemiology
Abstract: BackgroundThe Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12.MethodsThis study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD).Primary resultsAt baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine,
Published: 2021

2. Baseline brain function in the preadolescents of the ABCD Study

Author: Chaarani, B, Hahn, S, Allgaier, N, Adise, S, Owens, MM, Juliano, AC, Yuan, DK, Loso, H, Ivanciu, A, Albaugh, MD, Dumas, J, Mackey, S, Laurent, J, Ivanova, M, Hagler, DJ, Cornejo, MD, Hatton, S, Agrawal, A, Aguinaldo, L, Ahonen, L, Aklin, W, Anokhin, AP, Arroyo, J, Avenevoli, S, Babcock, D, Bagot, K, Baker, FC, Banich, MT, Barch, DM, Bartsch, H, Baskin-Sommers, A, Bjork, JM, Blachman-Demner, D, Bloch, M, Bogdan, R, Bookheimer, SY, Breslin, F, Brown, S, Calabro, FJ, Calhoun, V, Casey, BJ, Chang, L, Clark, DB, Cloak, C, Constable, RT, Constable, K, Corley, R, Cottler, LB, Coxe, S, Dagher, RK, Dale, AM, Dapretto, M, Delcarmen-Wiggins, R, Dick, AS, Do, EK, Dosenbach, NUF, Dowling, GJ, Edwards, S, Ernst, TM, Fair, DA, Fan, CC, Feczko, E, Feldstein-Ewing, SW, Florsheim, P, Foxe, JJ, Freedman, EG, Friedman, NP, Friedman-Hill, S, Fuemmeler, BF, Galvan, A, Gee, DG, Giedd, J, Glantz, M, Glaser, P, Godino, J, Gonzalez, M, Gonzalez, R, Grant, S, Gray, KM, Haist, F, Harms, MP, Hawes, S, Heath, AC, Heeringa, S, Heitzeg, MM, Hermosillo, R, Herting, MM, Hettema, JM, Hewitt, JK, Heyser, C, Hoffman, E, Howlett, K, Huber, RS, Huestis, MA, Hyde, LW, Iacono, WG, Infante, MA, Irfanoglu, O, Isaiah, A, and Iyengar, S
Subjects: Biological Psychology, Cognitive and Computational Psychology, Psychology, Mind and Body, Substance Misuse, Behavioral and Social Science, Clinical Research, Mental Health, Basic Behavioral and Social Science, Neurosciences, Drug Abuse (NIDA only), 1.2 Psychological and socioeconomic processes, Underpinning research, Neurological, Mental health, Adolescent, Adolescent Development, Brain, Child, Female, Humans, Magnetic Resonance Imaging, Male, Reference Values, ABCD Consortium, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract: The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.
Published: 2021

3. Learnt dynamics generalizes across tasks, datasets, and populations

Author: Mahmood, U., Rahman, M. M., Fedorov, A., Fu, Z., Calhoun, V. D., and Plis, S. M.
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: Differentiating multivariate dynamic signals is a difficult learning problem as the feature space may be large yet often only a few training examples are available. Traditional approaches to this problem either proceed from handcrafted features or require large datasets to combat the m >> n problem. In this paper, we show that the source of the problem---signal dynamics---can be used to our advantage and noticeably improve classification performance on a range of discrimination tasks when training data is scarce. We demonstrate that self-supervised pre-training guided by signal dynamics produces embedding that generalizes across tasks, datasets, data collection sites, and data distributions. We perform an extensive evaluation of this approach on a range of tasks including simulated data, keyword detection problem, and a range of functional neuroimaging data, where we show that a single embedding learnt on healthy subjects generalizes across a number of disorders, age groups, and datasets., Comment: 11 pages, 12 figures. arXiv admin note: text overlap with arXiv:1911.06813
Published: 2019

4. Brain charts for the human lifespan

Author: Bethlehem, R. A. I., Seidlitz, J., White, S. R., Vogel, J. W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-Gonzalez, A., Astle, D. E., Auyeung, B., Ayub, M., Bae, J., Ball, G., Baron-Cohen, S., Beare, R., Bedford, S. A., Benegal, V., Beyer, F., Blangero, J., Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, A., Costantino, M., Courchesne, E., Crivello, F., Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, S., Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, G., Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galan-Garcia, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, D. C., Goodyer, I. M., Grant, P. E., Groenewold, N. A., Gunning, F. M., Gur, R. E., Gur, R. C., Hammill, C. F., Hansson, O., Hedden, T., Heinz, A., Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, A. J., Holt, R., Huang, H., Im, K., Ipser, J., Jack, Jr, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, D. T., Kahn, R. S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, S., Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, M. V., Lv, J., Lynch, C., Mallard, T. T., Marcelis, M., Markello, R. D., Mathias, S. R., Mazoyer, B., McGuire, P., Meaney, M. J., Mechelli, A., Medic, N., Misic, B., Morgan, S. E., Mothersill, D., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, R., Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, C., Park, M. M., Paus, T., Pausova, Z., Paz-Linares, D., Pichet Binette, A., Pierce, K., Qian, X., Qiu, J., Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero-Garcia, R., Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, T. D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, G., Schöll, M., Sharp, D., Shinohara, R. T., Skoog, I., Smyser, C. D., Sperling, R. A., Stein, D. J., Stolicyn, A., Suckling, J., Sullivan, G., Taki, Y., Thyreau, B., Toro, R., Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, S. L., van Amelsvoort, T., Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, A., Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, E., Westwater, M. L., Whalley, H. C., Witte, A. V., Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, A., Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., and Alexander-Bloch, A. F.
Published: 2022
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5. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group

Author: Kelly, S, Jahanshad, N, Zalesky, A, Kochunov, P, Agartz, I, Alloza, C, Andreassen, OA, Arango, C, Banaj, N, Bouix, S, Bousman, CA, Brouwer, RM, Bruggemann, J, Bustillo, J, Cahn, W, Calhoun, V, Cannon, D, Carr, V, Catts, S, Chen, J, Chen, J-X, Chen, X, Chiapponi, C, Cho, Kl K, Ciullo, V, Corvin, AS, Crespo-Facorro, B, Cropley, V, De Rossi, P, Diaz-Caneja, CM, Dickie, EW, Ehrlich, S, Fan, F-M, Faskowitz, J, Fatouros-Bergman, H, Flyckt, L, Ford, JM, Fouche, J-P, Fukunaga, M, Gill, M, Glahn, DC, Gollub, R, Goudzwaard, ED, Guo, H, Gur, RE, Gur, RC, Gurholt, TP, Hashimoto, R, Hatton, SN, Henskens, FA, Hibar, DP, Hickie, IB, Hong, LE, Horacek, J, Howells, FM, Hulshoff Pol, HE, Hyde, CL, Isaev, D, Jablensky, A, Jansen, PR, Janssen, J, Jönsson, EG, Jung, LA, Kahn, RS, Kikinis, Z, Liu, K, Klauser, P, Knöchel, C, Kubicki, M, Lagopoulos, J, Langen, C, Lawrie, S, Lenroot, RK, Lim, KO, Lopez-Jaramillo, C, Lyall, A, Magnotta, V, Mandl, RCW, Mathalon, DH, McCarley, RW, McCarthy-Jones, S, McDonald, C, McEwen, S, McIntosh, A, Melicher, T, Mesholam-Gately, RI, Michie, PT, Mowry, B, Mueller, BA, Newell, DT, O'Donnell, P, Oertel-Knöchel, V, Oestreich, L, Paciga, SA, Pantelis, C, Pasternak, O, Pearlson, G, Pellicano, GR, Pereira, A, and Pineda Zapata, J
Subjects: Neurosciences, Brain Disorders, Mental Health, Serious Mental Illness, Biomedical Imaging, Schizophrenia, Clinical Research, Mental health, Adult, Aged, Aged, 80 and over, Brain, Cohort Studies, Corpus Callosum, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, White Matter, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2018

6. Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks

Author: Yang, H., primary, Ortiz-Bouza, M., additional, Vu, T., additional, Laport, F., additional, Calhoun, V. D., additional, Aviyente, S., additional, and Adali, T., additional
Published: 2024
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7. Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study

Author: Lisdahl, Krista M., Tapert, Susan, Sher, Kenneth J., Gonzalez, Raul, Nixon, Sara Jo, Feldstein Ewing, Sarah W., Conway, Kevin P., Wallace, Alex, Sullivan, Ryan, Hatcher, Kelah, Kaiver, Christine, Thompson, Wes, Reuter, Chase, Bartsch, Hauke, Wade, Natasha E., Jacobus, Joanna, Albaugh, M.D., Allgaier, N., Anokhin, A.P., Bagot, K., Baker, F.C., Banich, M.T., Barch, D.M., Baskin-Sommers, A., Breslin, F.J., Brown, S.A., Calhoun, V., Casey, B.J., Chaarani, B., Chang, L., Clark, D.B., Cloak, C., Constable, R.T., Cottler, L.B., Dagher, R.K., Dapretto, M., Dick, A., Do, E.K., Dosenbach, N.U.F., Dowling, G.J., Fair, D.A., Florsheim, P., Foxe, J.J., Freedman, E.G., Friedman, N.P., Garavan, H.P., Gee, D.G., Glantz, M.D., Glaser, P., Gonzalez, M.R., Gray, K.M., Grant, S., Haist, F., Hawes, S., Heeringa, S.G., Hermosillo, R., Herting, M.M., Hettema, J.M., Hewitt, J.K., Heyser, C., Hoffman, E.A., Howlett, K.D., Huber, R.S., Huestis, M.A., Hyde, L.W., Iacono, W.G., Isaiah, A., Ivanova, M.Y., James, R.S., Jernigan, T.L., Karcher, N.R., Kuperman, J.M., Laird, A.R., Larson, C.L., LeBlanc, K.H., Lopez, M.F., Luciana, M., Luna, B., Maes, H.H., Marshall, A.T., Mason, M.J., McGlade, E., Morris, A.S., Mulford, C., Nagel, B.J., Neigh, G., Palmer, C.E., Paulus, M.P., Pecheva, D., Prouty, D., Potter, A., Puttler, L.I., Rajapakse, N., Ross, J.M, Sanchez, M., Schirda, C., Schulenberg, J., Sheth, C., Shilling, P.D., Sowell, E.R., Speer, N., Squeglia, L., Sripada, C., Steinberg, J., Sutherland, M.T., Tomko, R., Uban, K., Vrieze, S., Weiss, S.R.B., Wing, D., Yurgelun-Todd, D.A., Zucker, R.A., and Heitzeg, Mary M.
Published: 2021
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8. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers

Author: Boen, R, Kaufmann, T, van der Meer, D, Frei, O, Agartz, I, Ames, D, Andersson, M, Armstrong, NJ, Artiges, E, Atkins, JR, Bauer, J, Benedetti, F, Boomsma, DI, Brodaty, H, Brosch, K, Buckner, RL, Cairns, MJ, Calhoun, V, Caspers, S, Cichon, S, Corvin, AP, Crespo-Facorro, B, Dannlowski, U, David, FS, de Geus, EJC, de Zubicaray, GI, Desrivieres, S, Doherty, JL, Donohoe, G, Ehrlich, S, Eising, E, Espeseth, T, Fisher, SE, Forstner, AJ, Fortaner-Uya, L, Frouin, V, Fukunaga, M, Ge, T, Glahn, DC, Goltermann, J, Grabe, HJ, Green, MJ, Groenewold, NA, Grotegerd, D, Grontvedt, GR, Hahn, T, Hashimoto, R, Hehir-Kwa, JY, Henskens, FA, Holmes, AJ, Haberg, AK, Haavik, J, Jacquemont, S, Jansen, A, Jockwitz, C, Joensson, EG, Kikuchi, M, Kircher, T, Kumar, K, Le Hellard, S, Leu, C, Linden, DE, Liu, J, Loughnan, R, Mather, KA, Mcmahon, KL, Mcrae, AF, Medland, SE, Meinert, S, Moreau, CA, Morris, DW, Mowry, BJ, Muehleisen, TW, Nenadic, I, Noethen, MM, Nyberg, L, Ophoff, RA, Owen, MJ, Pantelis, C, Paolini, M, Paus, T, Pausova, Z, Persson, K, Quide, Y, Marques, TR, Sachdev, PS, Sando, SB, Schall, U, Scott, RJ, Selbaek, G, Shumskaya, E, Silva, AI, Sisodiya, SM, Stein, F, Stein, DJ, Straube, B, Streit, F, Strike, LT, Teumer, A, Teutenberg, L, Thalamuthu, A, Tooney, PA, Tordesillas-Gutierrez, D, Trollor, JN, Van't Ent, D, van den Bree, MBM, van Haren, NEM, Vazquez-Bourgon, J, Voelzke, H, Wen, W, Wittfeld, K, Ching, CRK, Westlye, LT, Thompson, PM, Bearden, CE, Selmer, KK, Alnaes, D, Andreassen, OA, Sonderby, IE, Boen, R, Kaufmann, T, van der Meer, D, Frei, O, Agartz, I, Ames, D, Andersson, M, Armstrong, NJ, Artiges, E, Atkins, JR, Bauer, J, Benedetti, F, Boomsma, DI, Brodaty, H, Brosch, K, Buckner, RL, Cairns, MJ, Calhoun, V, Caspers, S, Cichon, S, Corvin, AP, Crespo-Facorro, B, Dannlowski, U, David, FS, de Geus, EJC, de Zubicaray, GI, Desrivieres, S, Doherty, JL, Donohoe, G, Ehrlich, S, Eising, E, Espeseth, T, Fisher, SE, Forstner, AJ, Fortaner-Uya, L, Frouin, V, Fukunaga, M, Ge, T, Glahn, DC, Goltermann, J, Grabe, HJ, Green, MJ, Groenewold, NA, Grotegerd, D, Grontvedt, GR, Hahn, T, Hashimoto, R, Hehir-Kwa, JY, Henskens, FA, Holmes, AJ, Haberg, AK, Haavik, J, Jacquemont, S, Jansen, A, Jockwitz, C, Joensson, EG, Kikuchi, M, Kircher, T, Kumar, K, Le Hellard, S, Leu, C, Linden, DE, Liu, J, Loughnan, R, Mather, KA, Mcmahon, KL, Mcrae, AF, Medland, SE, Meinert, S, Moreau, CA, Morris, DW, Mowry, BJ, Muehleisen, TW, Nenadic, I, Noethen, MM, Nyberg, L, Ophoff, RA, Owen, MJ, Pantelis, C, Paolini, M, Paus, T, Pausova, Z, Persson, K, Quide, Y, Marques, TR, Sachdev, PS, Sando, SB, Schall, U, Scott, RJ, Selbaek, G, Shumskaya, E, Silva, AI, Sisodiya, SM, Stein, F, Stein, DJ, Straube, B, Streit, F, Strike, LT, Teumer, A, Teutenberg, L, Thalamuthu, A, Tooney, PA, Tordesillas-Gutierrez, D, Trollor, JN, Van't Ent, D, van den Bree, MBM, van Haren, NEM, Vazquez-Bourgon, J, Voelzke, H, Wen, W, Wittfeld, K, Ching, CRK, Westlye, LT, Thompson, PM, Bearden, CE, Selmer, KK, Alnaes, D, Andreassen, OA, and Sonderby, IE
Abstract: BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
Published: 2024

9. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author: Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.
Abstract: The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
Published: 2024

10. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author: Poldrack, R. A., Markiewicz, C. J., Appelhoff, S., Ashar, Y. K., Auer, T., Baillet, S., Bansal, S., Beltrachini, L., Bertazzoli, G., Bhogawar, S., Blair, R. W., Bortoletto, M., Boudreau, M., Brooks, T. L., Bénar, C. G., Calhoun, V. D., Castelli, F. M., Clement, P., Cohen, A. L., Cohen-Adad, J., Dambrosio, S., Delorme, A., Devinsky, O., Draschkow, D., Duff, E. P., Dupre, E., Earl, E., Esteban, O., Feingold, F. W., Flandin, G., Galassi, A., Gallitto, G., Ganz, M., Gholam, J., Ghosh, S. S., Giacomel, A., Gillman, A. G., Gleeson, P., Gramfort, A., Guay, S., Guidali, G., Halchenko, Y. O., Handwerker, D. A., Hardcastle, N., Herholz, P., Hermes, D., Honey, C. J., Innis, R. B., Ioanas, H.-I., Jahn, A., Karakuzu, A., Keator, D. B., Kiar, G., Kincses, B., Laird, A. R., Lau, J. C., Lazari, A., Legarreta, J. H., Li, A., Li, X., Love, B. C., Lu, H., Maumet, C., Mazzamuto, G., Meisler, S. L., Mikkelsen, M., Mutsaerts, H., Nichols, T. E., Nikolaidis, A., Nilsonne, G., Niso, G., Norgaard, M., Okell, T. W., Oostenveld, R., Ort, E., Park, P. J., Pawlik, M., Pernet, C. R., Pestilli, F., (0000-0002-3201-6002) Petr, J., Phillips, C., Poline, J.-B., Pollonini, L., Raamana, P. R., Ritter, P., Rizzo, G., Robbins, K. A., Rockhill, A. P., Rogers, C., Rokem, A., Rorden, C., Routier, A., Saborit-Torres, J. M., Salo, T., Schirner, M., Smith, R. E., Spisak, T., Sprenger, J., Swann, N. C., Szinte, M., Takerkart, S., Thirion, B., Thomas, A. G., Torabian, S., Varoquaux, G., Vaya, M. D. L. I., Voytek, B., Welzel, J., Wilson, M., Hollander, G., Vega, A., Gorgolewski, K. J., Poldrack, R. A., Markiewicz, C. J., Appelhoff, S., Ashar, Y. K., Auer, T., Baillet, S., Bansal, S., Beltrachini, L., Bertazzoli, G., Bhogawar, S., Blair, R. W., Bortoletto, M., Boudreau, M., Brooks, T. L., Bénar, C. G., Calhoun, V. D., Castelli, F. M., Clement, P., Cohen, A. L., Cohen-Adad, J., Dambrosio, S., Delorme, A., Devinsky, O., Draschkow, D., Duff, E. P., Dupre, E., Earl, E., Esteban, O., Feingold, F. W., Flandin, G., Galassi, A., Gallitto, G., Ganz, M., Gholam, J., Ghosh, S. S., Giacomel, A., Gillman, A. G., Gleeson, P., Gramfort, A., Guay, S., Guidali, G., Halchenko, Y. O., Handwerker, D. A., Hardcastle, N., Herholz, P., Hermes, D., Honey, C. J., Innis, R. B., Ioanas, H.-I., Jahn, A., Karakuzu, A., Keator, D. B., Kiar, G., Kincses, B., Laird, A. R., Lau, J. C., Lazari, A., Legarreta, J. H., Li, A., Li, X., Love, B. C., Lu, H., Maumet, C., Mazzamuto, G., Meisler, S. L., Mikkelsen, M., Mutsaerts, H., Nichols, T. E., Nikolaidis, A., Nilsonne, G., Niso, G., Norgaard, M., Okell, T. W., Oostenveld, R., Ort, E., Park, P. J., Pawlik, M., Pernet, C. R., Pestilli, F., (0000-0002-3201-6002) Petr, J., Phillips, C., Poline, J.-B., Pollonini, L., Raamana, P. R., Ritter, P., Rizzo, G., Robbins, K. A., Rockhill, A. P., Rogers, C., Rokem, A., Rorden, C., Routier, A., Saborit-Torres, J. M., Salo, T., Schirner, M., Smith, R. E., Spisak, T., Sprenger, J., Swann, N. C., Szinte, M., Takerkart, S., Thirion, B., Thomas, A. G., Torabian, S., Varoquaux, G., Vaya, M. D. L. I., Voytek, B., Welzel, J., Wilson, M., Hollander, G., Vega, A., and Gorgolewski, K. J.
Abstract: The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, and the mechanisms by which it has been extended. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
Published: 2024

11. Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls

Author: Verdijk, J., Mortel, L.A. van de, Doesschate, F. Ten, Pottkämper, J.C.M., Stuiver, S., Bruin, W.B., Abbott, C.C., Argyelan, M., Ousdal, O.T., Bartsch, H., Narr, K., Tendolkar, I., Calhoun, V., Lukemire, J., Guo, Y., Oltedal, L., Wingen, G.A. van, Waarde, J.A. van, Verdijk, J., Mortel, L.A. van de, Doesschate, F. Ten, Pottkämper, J.C.M., Stuiver, S., Bruin, W.B., Abbott, C.C., Argyelan, M., Ousdal, O.T., Bartsch, H., Narr, K., Tendolkar, I., Calhoun, V., Lukemire, J., Guo, Y., Oltedal, L., Wingen, G.A. van, and Waarde, J.A. van
Abstract: Contains fulltext : 305052.pdf (Publisher’s version ) (Open Access), OBJECTIVE: Electroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study. METHODS: Functional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed. RESULTS: Within-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes. CONCLUSION: DMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects.
Published: 2024

12. MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway:Role in lateral ventricles and corpus callosum volume

Author: Blokland, G. A.M., Maleki, N., Jovicich, J., Mesholam-Gately, R. I., DeLisi, L. E., Turner, J. A., Shenton, M. E., Voineskos, A. N., Kahn, R. S., Roffman, J. L., Holt, D. J., Ehrlich, S., Kikinis, Z., Dazzan, P., Murray, R. M., Lee, J., Sim, K., Lam, M., de Zwarte, S. M.C., Walton, E., Kelly, S., Picchioni, M. M., Bramon, E., Makris, N., David, A. S., Mondelli, V., Reinders, A. A.T.S., Oykhman, E., Morris, D. W., Gill, M., Corvin, A. P., Cahn, W., Ho, N., Liu, J., Gollub, R. L., Manoach, D. S., Calhoun, V. D., Sponheim, S. R., Buka, S. L., Cherkerzian, S., Thermenos, H. W., Dickie, E. W., Ciufolini, S., Reis Marques, T., Crossley, N. A., Purcell, S. M., Smoller, J. W., van Haren, N. E.M., Toulopoulou, T., Donohoe, G., Goldstein, J. M., Keshavan, M. S., Petryshen, T. L., del Re, E. C., Blokland, G. A.M., Maleki, N., Jovicich, J., Mesholam-Gately, R. I., DeLisi, L. E., Turner, J. A., Shenton, M. E., Voineskos, A. N., Kahn, R. S., Roffman, J. L., Holt, D. J., Ehrlich, S., Kikinis, Z., Dazzan, P., Murray, R. M., Lee, J., Sim, K., Lam, M., de Zwarte, S. M.C., Walton, E., Kelly, S., Picchioni, M. M., Bramon, E., Makris, N., David, A. S., Mondelli, V., Reinders, A. A.T.S., Oykhman, E., Morris, D. W., Gill, M., Corvin, A. P., Cahn, W., Ho, N., Liu, J., Gollub, R. L., Manoach, D. S., Calhoun, V. D., Sponheim, S. R., Buka, S. L., Cherkerzian, S., Thermenos, H. W., Dickie, E. W., Ciufolini, S., Reis Marques, T., Crossley, N. A., Purcell, S. M., Smoller, J. W., van Haren, N. E.M., Toulopoulou, T., Donohoe, G., Goldstein, J. M., Keshavan, M. S., Petryshen, T. L., and del Re, E. C.
Abstract: Background/Objective:Enlarged lateral ventricle (LV) volume and decreased volume in the corpus callosum (CC) are hallmarks of schizophrenia (SZ). We previously showed an inverse correlation between LV and CC volumes in SZ, with global functioning decreasing with increased LV volume. This study investigates the relationship between LV volume, CC abnormalities, and the microRNA MIR137 and its regulated genes in SZ, because of MIR137’s essential role in neurodevelopment. Methods:Participants were 1224 SZ probands and 1466 unaffected controls from the GENUS Consortium. Brain MRI scans, genotype, and clinical data were harmonized across cohorts and employed in the analyses. Results:Increased LV volumes and decreased CC central, mid-anterior, and mid-posterior volumes were observed in SZ probands. The MIR137-regulated ephrin pathway was significantly associated with CC:LV ratio, explaining a significant proportion (3.42 %) of CC:LV variance, and more than for LV and CC separately. Other pathways explained variance in either CC or LV, but not both. CC:LV ratio was also positively correlated with Global Assessment of Functioning, supporting previous subsample findings. SNP-based heritability estimates were higher for CC central:LV ratio (0.79) compared to CC or LV separately.Discussion:Our results indicate that the CC:LV ratio is highly heritable, influenced in part by variation in the MIR137-regulated ephrin pathway. Findings suggest that the CC:LV ratio may be a risk indicator in SZ that correlates with global functioning.
Published: 2024

13. Publisher Correction: Brain charts for the human lifespan

Author: Bethlehem, R. A. I., Seidlitz, J., White, S. R., Vogel, J. W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-Gonzalez, A., Astle, D. E., Auyeung, B., Ayub, M., Bae, J., Ball, G., Baron-Cohen, S., Beare, R., Bedford, S. A., Benegal, V., Beyer, F., Blangero, J., Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, A., Costantino, M., Courchesne, E., Crivello, F., Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, S., Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, G., Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galan-Garcia, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, D. C., Goodyer, I. M., Grant, P. E., Groenewold, N. A., Gunning, F. M., Gur, R. E., Gur, R. C., Hammill, C. F., Hansson, O., Hedden, T., Heinz, A., Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, A. J., Holt, R., Huang, H., Im, K., Ipser, J., Jack, Jr, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, D. T., Kahn, R. S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, S., Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, M. V., Lv, J., Lynch, C., Mallard, T. T., Marcelis, M., Markello, R. D., Mathias, S. R., Mazoyer, B., McGuire, P., Meaney, M. J., Mechelli, A., Medic, N., Misic, B., Morgan, S. E., Mothersill, D., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, R., Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, C., Park, M. M., Paus, T., Pausova, Z., Paz-Linares, D., Pichet Binette, A., Pierce, K., Qian, X., Qiu, J., Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero-Garcia, R., Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, T. D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, G., Schöll, M., Sharp, D., Shinohara, R. T., Skoog, I., Smyser, C. D., Sperling, R. A., Stein, D. J., Stolicyn, A., Suckling, J., Sullivan, G., Taki, Y., Thyreau, B., Toro, R., Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, S. L., van Amelsvoort, T., Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, A., Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, E., Westwater, M. L., Whalley, H. C., Witte, A. V., Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, A., Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., and Alexander-Bloch, A. F.
Published: 2022
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14. REGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS

Author: Yang, H., primary, Gabrielson, B., additional, Calhoun, V. D., additional, and Adali, T., additional
Published: 2023
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15. Identifying canonical and replicable multi‐scale intrinsic connectivity networks in 100k+ resting‐state fMRI datasets

Author: Iraji, A., primary, Fu, Z., additional, Faghiri, A., additional, Duda, M., additional, Chen, J., additional, Rachakonda, S., additional, DeRamus, T., additional, Kochunov, P., additional, Adhikari, B. M., additional, Belger, A., additional, Ford, J. M., additional, Mathalon, D. H., additional, Pearlson, G. D., additional, Potkin, S. G., additional, Preda, A., additional, Turner, J. A., additional, van Erp, T. G. M., additional, Bustillo, J. R., additional, Yang, K., additional, Ishizuka, K., additional, Faria, A., additional, Sawa, A., additional, Hutchison, K., additional, Osuch, E. A., additional, Theberge, J., additional, Abbott, C., additional, Mueller, B. A., additional, Zhi, D., additional, Zhuo, C., additional, Liu, S., additional, Xu, Y., additional, Salman, M., additional, Liu, J., additional, Du, Y., additional, Sui, J., additional, Adali, T., additional, and Calhoun, V. D., additional
Published: 2023
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16. Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion

Author: Borsoi, R. A., primary, Lehmann, I., additional, Akhonda, M. A. B. S., additional, Calhoun, V. D., additional, Usevich, K., additional, Brie, D., additional, and Adali, T., additional
Published: 2023
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17. Constrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data

Author: Yang, H., primary, Ghayem, F., additional, Gabrielson, B., additional, Akhonda, M. A. B. S., additional, Calhoun, V. D., additional, and Adali, T., additional
Published: 2023
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18. New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning

Author: Ghayem, F., primary, Yang, H., additional, Kantar, F., additional, Kim, S.-J., additional, Calhoun, V. D., additional, and Adali, T., additional
Published: 2023
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19. Decreased hemispheric connectivity and decreased intra- and inter- hemisphere asymmetry of resting state functional network connectivity in schizophrenia

Author: Agcaoglu, O., Miller, R., Damaraju, E., Rashid, B., Bustillo, J., Cetin, M. S., Van Erp, T. G. M., McEwen, S., Preda, A., Ford, J. M., Lim, K. O., Manoach, D. S., Mathalon, D. H., Potkin, S. G., and Calhoun, V. D.
Published: 2018
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20. Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Author: Constantinides, C, Han, LKM, Alloza, C, Antonucci, LA, Arango, C, Ayesa-Arriola, R, Banaj, N, Bertolino, A, Borgwardt, S, Bruggemann, J, Bustillo, J, Bykhovski, O, Calhoun, V, Carr, V, Catts, S, Chung, Y-C, Crespo-Facorro, B, Diaz-Caneja, CM, Donohoe, G, Du Plessis, S, Edmond, J, Ehrlich, S, Emsley, R, Eyler, LT, Fuentes-Claramonte, P, Georgiadis, F, Green, M, Guerrero-Pedraza, A, Ha, M, Hahn, T, Henskens, FA, Holleran, L, Homan, S, Homan, P, Jahanshad, N, Janssen, J, Ji, E, Kaiser, S, Kaleda, V, Kim, M, Kim, W-S, Kirschner, M, Kochunov, P, Kwak, YB, Kwon, JS, Lebedeva, I, Liu, J, Mitchie, P, Michielse, S, Mothersill, D, Mowry, B, de la Foz, VO-G, Pantelis, C, Pergola, G, Piras, F, Pomarol-Clotet, E, Preda, A, Quide, Y, Rasser, PE, Rootes-Murdy, K, Salvador, R, Sangiuliano, M, Sarro, S, Schall, U, Schmidt, A, Scott, RJ, Selvaggi, P, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Thomopoulos, S, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, van Amelsvoort, T, Vazquez-Bourgon, J, Vecchio, D, Voineskos, A, Weickert, CS, Weickert, T, Thompson, PM, Schmaal, L, van Erp, TGM, Turner, J, Cole, JH, Dima, D, Walton, E, Constantinides, C, Han, LKM, Alloza, C, Antonucci, LA, Arango, C, Ayesa-Arriola, R, Banaj, N, Bertolino, A, Borgwardt, S, Bruggemann, J, Bustillo, J, Bykhovski, O, Calhoun, V, Carr, V, Catts, S, Chung, Y-C, Crespo-Facorro, B, Diaz-Caneja, CM, Donohoe, G, Du Plessis, S, Edmond, J, Ehrlich, S, Emsley, R, Eyler, LT, Fuentes-Claramonte, P, Georgiadis, F, Green, M, Guerrero-Pedraza, A, Ha, M, Hahn, T, Henskens, FA, Holleran, L, Homan, S, Homan, P, Jahanshad, N, Janssen, J, Ji, E, Kaiser, S, Kaleda, V, Kim, M, Kim, W-S, Kirschner, M, Kochunov, P, Kwak, YB, Kwon, JS, Lebedeva, I, Liu, J, Mitchie, P, Michielse, S, Mothersill, D, Mowry, B, de la Foz, VO-G, Pantelis, C, Pergola, G, Piras, F, Pomarol-Clotet, E, Preda, A, Quide, Y, Rasser, PE, Rootes-Murdy, K, Salvador, R, Sangiuliano, M, Sarro, S, Schall, U, Schmidt, A, Scott, RJ, Selvaggi, P, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Thomopoulos, S, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, van Amelsvoort, T, Vazquez-Bourgon, J, Vecchio, D, Voineskos, A, Weickert, CS, Weickert, T, Thompson, PM, Schmaal, L, van Erp, TGM, Turner, J, Cole, JH, Dima, D, and Walton, E
Abstract: Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.
Published: 2023

21. Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets.

Author: Iraji, A, Iraji, A, Fu, Z, Faghiri, A, Duda, M, Chen, J, Rachakonda, S, DeRamus, T, Kochunov, P, Adhikari, B, Belger, A, Ford, J, Bustillo, J, Yang, K, Ishizuka, K, Faria, A, Sawa, A, Hutchison, K, Osuch, E, Theberge, J, Abbott, C, Mueller, B, Zhi, D, Zhuo, C, Liu, S, Xu, Y, Salman, M, Liu, J, Du, Y, Sui, J, Adali, T, Calhoun, V, Pearlson, G, Potkin, S, Turner, J, Mathalon, Daniel, Van Erp, Theodorus, Preda, Adrian, Iraji, A, Iraji, A, Fu, Z, Faghiri, A, Duda, M, Chen, J, Rachakonda, S, DeRamus, T, Kochunov, P, Adhikari, B, Belger, A, Ford, J, Bustillo, J, Yang, K, Ishizuka, K, Faria, A, Sawa, A, Hutchison, K, Osuch, E, Theberge, J, Abbott, C, Mueller, B, Zhi, D, Zhuo, C, Liu, S, Xu, Y, Salman, M, Liu, J, Du, Y, Sui, J, Adali, T, Calhoun, V, Pearlson, G, Potkin, S, Turner, J, Mathalon, Daniel, Van Erp, Theodorus, and Preda, Adrian
Abstract: Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICNs subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.
Published: 2023

22. Identification of neurobiology-based cognition-related biotypes using data-driven techniques and multi-scale intrinsic connectivity networks in psychotic disorders

Author: Camazón, P. Andrés, primary, Ballem, R., additional, Chen, J., additional, Diaz-Caneja, C. Martinez, additional, Campayo, J. Suarez, additional, Calhoun, V., additional, and Iraji, A., additional
Published: 2023
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23. Source-Based Morphometry Multivariate Approach to Analyze [123I]FP-CIT SPECT Imaging

Author: Premi, Enrico, Calhoun, V. D., Garibotto, V., Turrone, R., Alberici, A., Cottini, E., Pilotto, A., Gazzina, S., Magoni, M., Paghera, B., Borroni, B., and Padovani, A.
Published: 2017
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24. EEG Signatures of Dynamic Functional Network Connectivity States

Author: Allen, E. A., Damaraju, E., Eichele, T., Wu, L., and Calhoun, V. D.
Published: 2017
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25. Increased spatial granularity of left brain activation and unique age/gender signatures: a 4D frequency domain approach to cerebral lateralization at rest

Author: Agcaoglu, O., Miller, R., Mayer, A. R., Hugdahl, K., and Calhoun, V. D.
Published: 2016
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26. Evaluation of Functional Network Connectivity in Event-related FMRI Data Based on ICA and Time-frequency Granger Causality

Author: Havlicek, M., Jan, J., Calhoun, V. D., Brazdil, M., Mikl, M., Magjarevic, Ratko, Dössel, Olaf, editor, and Schlegel, Wolfgang C., editor
Published: 2010
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27. Corrigendum to “Lateralization of resting state networks and relationship to age and gender” [NeuroImage 104 (2015) 310–325]

Author: Agcaoglu, O., Miller, R., Mayer, A. R., Hugdahl, K., and Calhoun, V. D.
Published: 2018
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28. Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium

Author: Walton, E., Hibar, D. P., van Erp, T. G. M., Potkin, S. G., Roiz-Santiañez, R., Crespo-Facorro, B., Suarez-Pinilla, P., van Haren, N. E. M., de Zwarte, S. M. C., Kahn, R. S., Cahn, W., Doan, N. T., Jørgensen, K. N., Gurholt, T. P., Agartz, I., Andreassen, O. A., Westlye, L. T., Melle, I., Berg, A. O., Morch-Johnsen, L., Færden, A., Flyckt, L., Fatouros-Bergman, H., Jönsson, E. G., Hashimoto, R., Yamamori, H., Fukunaga, M., Jahanshad, N., De Rossi, P., Piras, F., Banaj, N., Spalletta, G., Gur, R. E., Gur, R. C., Wolf, D. H., Satterthwaite, T. D., Beard, L. M., Sommer, I. E., Koops, S., Gruber, O., Richter, A., Krämer, B., Kelly, S., Donohoe, G., McDonald, C., Cannon, D. M., Corvin, A., Gill, M., Di Giorgio, A., Bertolino, A., Lawrie, S., Nickson, T., Whalley, H. C., Neilson, E., Calhoun, V. D., Thompson, P. M., Turner, J. A., and Ehrlich, S.
Published: 2018
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29. An ICA-based framework for joint analysis of cognitive scores and MEG event-related fields

Author: Boonyakitanont, P., primary, Gabrielson, B., additional, Belyaeva, I., additional, Olikkal, P., additional, Songsiri, J., additional, Wang, Y. P., additional, Wilson, T. W., additional, Calhoun, V. D., additional, Stephen, J. M., additional, and Adali, T., additional
Published: 2022
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30. Age-related network connectivity pattern changes are associated with risk for psychosis

Author: Passiatore, R., primary, Antonucci, L., additional, Deramus, T., additional, Fazio, L., additional, Stolfa, G., additional, Andriola, I., additional, Sangiuliano, M., additional, Altamura, M., additional, Saponaro, A., additional, Brudaglio, F., additional, Carofiglio, A., additional, Popolizio, T., additional, Sambataro, F., additional, Blasi, G., additional, Bertolino, A., additional, Calhoun, V., additional, and Pergola, G., additional
Published: 2022
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31. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Author: Dima, D., Modabbernia, A., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dannlowski, U., Dale, A.M., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Kalnin, A., Naaijen, J., Klein, M., Thompson, P.M., Frangou, S., Dima, D., Modabbernia, A., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dannlowski, U., Dale, A.M., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Kalnin, A., Naaijen, J., Klein, M., Thompson, P.M., and Frangou, S.
Abstract: Contains fulltext : 245411.pdf (Publisher’s version ) (Open Access), Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
Published: 2022

32. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Author: Frangou, S., Modabbernia, A., Williams, S.C.R., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dale, A.M., Dannlowski, U., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Klein, M., Frangou, S., Modabbernia, A., Williams, S.C.R., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dale, A.M., Dannlowski, U., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., and Klein, M.
Abstract: Contains fulltext : 245396.pdf (Publisher’s version ) (Open Access), Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
Published: 2022

33. Reproducibility in the absence of selective reporting: An illustration from large-scale brain asymmetry research

Author: Kong, XZ, Francks, C, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Asherson, P, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Cannon, DM, Caparelli, EC, Castellanos, FX, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dannlowski, U, de Bruttopilo, SA, de Zeeuw, P, Deary, IJ, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Flint, C, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, JM, Garavan, H, do Santos Garcia, D, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, del Carmen Valdés Hernández, M, Kong, XZ, Francks, C, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Asherson, P, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Cannon, DM, Caparelli, EC, Castellanos, FX, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dannlowski, U, de Bruttopilo, SA, de Zeeuw, P, Deary, IJ, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Flint, C, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, JM, Garavan, H, do Santos Garcia, D, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, and del Carmen Valdés Hernández, M
Published: 2022

34. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Author: Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Frangou, S, Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Frangou, S
Abstract: Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
Published: 2022

35. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Author: Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Dima, D, Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Dima, D
Abstract: Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
Published: 2022

36. Global urbanicity is associated with brain and behaviour in young people

Author: Xu, J, Liu, X, Li, Q., Goldblatt, R., Qin, W., Liu, F., Chu, C., Luo, Q., Ing, A., Guo, L., Liu, N., Liu, H., Huang, C., Cheng, J., Wang, M., Geng, Z., Zhu, W., Zhang, B., Liao, W., Qiu, S., Zhang, H, Xu, X., Yu, Y, Gao, B., Han, T., Cui, G., Chen, F., Xian, J., Li, J., Zhang, J., Zuo, X.N., Wang, D., Shen, W., Miao, Y., Yuan, F., Lui, S., Zhang, X., Xu, K., Zhang, L., Ye, Z., Banaschewski, T., Barker, G.J., Bokde, A.L., Flor, H., Grigis, A., Garavan, H., Gowland, P., Heinz, A., Brühl, R., Martinot, J.L., Artiges, E., Nees, F., Orfanos, D.P., Lemaitre, H., Paus, T., Poustka, L., Robinson, L., Hohmann, S., Fröhner, J.H., Smolka, M.N., Walter, H., Whelan, R., Winterer, J., Patrick, K., Calhoun, V., Li, M.J., Liang, M., Gong, P., Barker, E.D., Clinton, N., Marquand, A.F., Yu, L., Yu, C., Schumann, G., Xu, J, Liu, X, Li, Q., Goldblatt, R., Qin, W., Liu, F., Chu, C., Luo, Q., Ing, A., Guo, L., Liu, N., Liu, H., Huang, C., Cheng, J., Wang, M., Geng, Z., Zhu, W., Zhang, B., Liao, W., Qiu, S., Zhang, H, Xu, X., Yu, Y, Gao, B., Han, T., Cui, G., Chen, F., Xian, J., Li, J., Zhang, J., Zuo, X.N., Wang, D., Shen, W., Miao, Y., Yuan, F., Lui, S., Zhang, X., Xu, K., Zhang, L., Ye, Z., Banaschewski, T., Barker, G.J., Bokde, A.L., Flor, H., Grigis, A., Garavan, H., Gowland, P., Heinz, A., Brühl, R., Martinot, J.L., Artiges, E., Nees, F., Orfanos, D.P., Lemaitre, H., Paus, T., Poustka, L., Robinson, L., Hohmann, S., Fröhner, J.H., Smolka, M.N., Walter, H., Whelan, R., Winterer, J., Patrick, K., Calhoun, V., Li, M.J., Liang, M., Gong, P., Barker, E.D., Clinton, N., Marquand, A.F., Yu, L., Yu, C., and Schumann, G.
Abstract: Item does not contain fulltext, Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.
Published: 2022

37. Brain charts for the human lifespan

Author: British Academy, Autism Research Trust, National Institute of Mental Health (US), UK Research and Innovation, Medical Research Council (UK), National Institute for Health and Care Research (US), Wellcome Trust, University of Cambridge, Cambridge Biomedical Research Centre, Bethlehem, Richard A. I., Seidlitz, J., White, S. R., Vogel, Jacob W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-González, A., Astle, D. E., Auyeung, Bonnie, Ayub, Muhammad, Bae, J., Ball, G, Baron-Cohen, Simon, Beare, R., Bedford, S. A., Benegal, V., Beyer, Frauke, Blangero, John, Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, Aiden, Costantino, M., Courchesne, E., Crivello, Fabrice, Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, Sylvane, Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, Gary, Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galán-García, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, David C., Goodyer, I. M., Grant, P. E., Groenewold, Nynke A., Gunning, F. M., Gur, Rachel E., Gur, Ruben C., Hammill, C. F., Hansson, Oskar, Hedden, T., Heinz, Andreas, Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, Avram J., Holt, Rosemary, Huang, Hailiang, Im, K., Ipser, J., Jack, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, David T. W., Kahn, René S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, Silke, Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, Michael, V., Lv, J., Lynch, Christopher D., Mallard, T. T., Marcelis, Machteld, Markello, R. D., Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, M. J., Mechelli, Andrea, Medic, N., Misic, B., Morgan, S. E., Mothersill, David O., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, Rik, Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, Christos, Park, M. M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, D., Pichler, Alexander, Pierce, K., Qian, X., Qiu, Jing, Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero García, Rafael, Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, Theodore D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, Gunter, Schöll, Michael, Sharp, D., Shinohara, R. T., Skoog, Ingmar, Smyser, C. D., Sperling, R. A., Stein, Dan J., Stolicyn, A., Suckling, John, Sullivan, G., Taki, Y., Thyreau, B., Toro, Raquel del, Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, Arno, Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, Eric, Westwater, M. L., Whalley, Heather, Witte, A. Veronica, Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, Anna, Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., Alexander-Bloch, A. F., British Academy, Autism Research Trust, National Institute of Mental Health (US), UK Research and Innovation, Medical Research Council (UK), National Institute for Health and Care Research (US), Wellcome Trust, University of Cambridge, Cambridge Biomedical Research Centre, Bethlehem, Richard A. I., Seidlitz, J., White, S. R., Vogel, Jacob W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-González, A., Astle, D. E., Auyeung, Bonnie, Ayub, Muhammad, Bae, J., Ball, G, Baron-Cohen, Simon, Beare, R., Bedford, S. A., Benegal, V., Beyer, Frauke, Blangero, John, Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, Aiden, Costantino, M., Courchesne, E., Crivello, Fabrice, Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, Sylvane, Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, Gary, Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galán-García, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, David C., Goodyer, I. M., Grant, P. E., Groenewold, Nynke A., Gunning, F. M., Gur, Rachel E., Gur, Ruben C., Hammill, C. F., Hansson, Oskar, Hedden, T., Heinz, Andreas, Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, Avram J., Holt, Rosemary, Huang, Hailiang, Im, K., Ipser, J., Jack, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, David T. W., Kahn, René S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, Silke, Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, Michael, V., Lv, J., Lynch, Christopher D., Mallard, T. T., Marcelis, Machteld, Markello, R. D., Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, M. J., Mechelli, Andrea, Medic, N., Misic, B., Morgan, S. E., Mothersill, David O., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, Rik, Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, Christos, Park, M. M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, D., Pichler, Alexander, Pierce, K., Qian, X., Qiu, Jing, Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero García, Rafael, Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, Theodore D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, Gunter, Schöll, Michael, Sharp, D., Shinohara, R. T., Skoog, Ingmar, Smyser, C. D., Sperling, R. A., Stein, Dan J., Stolicyn, A., Suckling, John, Sullivan, G., Taki, Y., Thyreau, B., Toro, Raquel del, Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, Arno, Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, Eric, Westwater, M. L., Whalley, Heather, Witte, A. Veronica, Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, Anna, Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., and Alexander-Bloch, A. F.
Abstract: Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
Published: 2022

38. Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI Data

Author: Yang, H., primary, Akhonda, M. A. B. S., additional, Ghayem, F., additional, Long, Q., additional, Calhoun, V. D., additional, and Adali, T., additional
Published: 2022
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39. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

Author: van Erp, T GM, Hibar, D P, Rasmussen, J M, Glahn, D C, Pearlson, G D, Andreassen, O A, Agartz, I, Westlye, L T, Haukvik, U K, Dale, A M, Melle, I, Hartberg, C B, Gruber, O, Kraemer, B, Zilles, D, Donohoe, G, Kelly, S, McDonald, C, Morris, D W, Cannon, D M, Corvin, A, Machielsen, M WJ, Koenders, L, de Haan, L, Veltman, D J, Satterthwaite, T D, Wolf, D H, Gur, R C, Gur, R E, Potkin, S G, Mathalon, D H, Mueller, B A, Preda, A, Macciardi, F, Ehrlich, S, Walton, E, Hass, J, Calhoun, V D, Bockholt, H J, Sponheim, S R, Shoemaker, J M, van Haren, N EM, Pol, H EH, Ophoff, R A, Kahn, R S, Roiz-Santiañez, R, Crespo-Facorro, B, Wang, L, Alpert, K I, Jönsson, E G, Dimitrova, R, Bois, C, Whalley, H C, McIntosh, A M, Lawrie, S M, Hashimoto, R, Thompson, P M, and Turner, J A
Published: 2016
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40. Altered regional cortical thickness and subcortical volume in women with primary dysmenorrhoea

Author: Liu, P., Yang, J., Wang, G., Liu, Y., Liu, X., Jin, L., Liang, F., Qin, W., and Calhoun, V. D.
Published: 2016
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41. Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine in humans

Author: Driesen, N R, McCarthy, G, Bhagwagar, Z, Bloch, M, Calhoun, V, D'Souza, D C, Gueorguieva, R, He, G, Ramachandran, R, Suckow, R F, Anticevic, A, Morgan, P T, and Krystal, J H
Published: 2013
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42. Nonlinear Functional Network Connectivity in Resting Fmri Data

Author: Motlaghian, S. M., primary, Belger, A., additional, Bustillo, J. R., additional, Ford, J. M., additional, Lim, K., additional, Mathalon, D. H., additional, Mueller, B. A., additional, O’Leary, D., additional, Pearlson, G., additional, Potkin, S. G., additional, Preda, A., additional, van Erp, T.G., additional, and Calhoun, V. D., additional
Published: 2021
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43. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author: Jia, T, Chu, C, Liu, Y, van Dongen, J, Papastergios, E, Armstrong, NJ, Bastin, ME, Carrillo-Roa, T, den Braber, A, Harris, M, Jansen, R, Liu, J, Luciano, M, Ori, APS, Santianez, RR, Ruggeri, B, Sarkisyan, D, Shin, J, Sungeun, K, Gutierrez, DT, van't Ent, D, Ames, D, Artiges, E, Bakalkin, G, Banaschewski, T, Bokde, ALW, Brodaty, H, Bromberg, U, Brouwer, R, Buchel, C, Quinlan, EB, Cahn, W, de Zubicaray, G, Ehrlich, S, Ekstrom, TJ, Flor, H, Frohner, JH, Frouin, V, Garavan, H, Gowland, P, Heinz, A, Hoare, J, Ittermann, B, Jahanshad, N, Jiang, J, Kwok, JB, Martin, NG, Martinot, J-L, Mather, KA, McMahon, KL, McRae, AF, Nees, F, Orfanos, DP, Paus, T, Poustka, L, Samann, PG, Schofield, PR, Smolka, MN, Stein, DJ, Strike, LT, Teeuw, J, Thalamuthu, A, Trollor, J, Walter, H, Wardlaw, JM, Wen, W, Whelan, R, Apostolova, LG, Binder, EB, Boomsma, D, Calhoun, V, Crespo-Facorro, B, Deary, IJ, Pol, HH, Ophoff, RA, Pausova, Z, Sachdev, PS, Saykin, A, Wright, MJ, Thompson, PM, Schumann, G, Desrivieres, S, Jia, T, Chu, C, Liu, Y, van Dongen, J, Papastergios, E, Armstrong, NJ, Bastin, ME, Carrillo-Roa, T, den Braber, A, Harris, M, Jansen, R, Liu, J, Luciano, M, Ori, APS, Santianez, RR, Ruggeri, B, Sarkisyan, D, Shin, J, Sungeun, K, Gutierrez, DT, van't Ent, D, Ames, D, Artiges, E, Bakalkin, G, Banaschewski, T, Bokde, ALW, Brodaty, H, Bromberg, U, Brouwer, R, Buchel, C, Quinlan, EB, Cahn, W, de Zubicaray, G, Ehrlich, S, Ekstrom, TJ, Flor, H, Frohner, JH, Frouin, V, Garavan, H, Gowland, P, Heinz, A, Hoare, J, Ittermann, B, Jahanshad, N, Jiang, J, Kwok, JB, Martin, NG, Martinot, J-L, Mather, KA, McMahon, KL, McRae, AF, Nees, F, Orfanos, DP, Paus, T, Poustka, L, Samann, PG, Schofield, PR, Smolka, MN, Stein, DJ, Strike, LT, Teeuw, J, Thalamuthu, A, Trollor, J, Walter, H, Wardlaw, JM, Wen, W, Whelan, R, Apostolova, LG, Binder, EB, Boomsma, D, Calhoun, V, Crespo-Facorro, B, Deary, IJ, Pol, HH, Ophoff, RA, Pausova, Z, Sachdev, PS, Saykin, A, Wright, MJ, Thompson, PM, Schumann, G, and Desrivieres, S
Abstract: DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.
Published: 2021

44. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author: Jia, T., Chu, C., Liu, Y., van Dongen, J., Papastergios, E., Armstrong, Nicola, Bastin, M.E., Carrillo-Roa, T., den Braber, A., Harris, M., Jansen, R., Liu, J., Luciano, M., Ori, A.P.S., Roiz Santiañez, R., Ruggeri, B., Sarkisyan, D., Shin, J., Sungeun, K., Tordesillas Gutiérrez, D., van’t Ent, D., Ames, D., Artiges, E., Bakalkin, G., Banaschewski, T., Bokde, A.L.W., Brodaty, H., Bromberg, U., Brouwer, R., Büchel, C., Burke Quinlan, E., Cahn, W., de Zubicaray, G.I., Ehrlich, S., Ekström, T.J., Flor, H., Fröhner, J.H., Frouin, V., Garavan, H., Gowland, P., Heinz, A., Hoare, J., Ittermann, B., Jahanshad, N., Jiang, J., Kwok, J.B., Martin, N.G., Martinot, J.L., Mather, K.A., McMahon, K.L., McRae, A.F., Nees, F., Papadopoulos Orfanos, D., Paus, T., Poustka, L., Sämann, P.G., Schofield, P.R., Smolka, M.N., Stein, D.J., Strike, L.T., Teeuw, J., Thalamuthu, A., Trollor, J., Walter, H., Wardlaw, J.M., Wen, W., Whelan, R., Apostolova, L.G., Binder, E.B., Boomsma, D.I., Calhoun, V., Crespo-Facorro, B., Deary, I.J., Hulshoff Pol, H., Ophoff, R.A., Pausova, Z., Sachdev, P.S., Saykin, A., Wright, M.J., Thompson, P.M., Schumann, G., Desrivières, S., Jia, T., Chu, C., Liu, Y., van Dongen, J., Papastergios, E., Armstrong, Nicola, Bastin, M.E., Carrillo-Roa, T., den Braber, A., Harris, M., Jansen, R., Liu, J., Luciano, M., Ori, A.P.S., Roiz Santiañez, R., Ruggeri, B., Sarkisyan, D., Shin, J., Sungeun, K., Tordesillas Gutiérrez, D., van’t Ent, D., Ames, D., Artiges, E., Bakalkin, G., Banaschewski, T., Bokde, A.L.W., Brodaty, H., Bromberg, U., Brouwer, R., Büchel, C., Burke Quinlan, E., Cahn, W., de Zubicaray, G.I., Ehrlich, S., Ekström, T.J., Flor, H., Fröhner, J.H., Frouin, V., Garavan, H., Gowland, P., Heinz, A., Hoare, J., Ittermann, B., Jahanshad, N., Jiang, J., Kwok, J.B., Martin, N.G., Martinot, J.L., Mather, K.A., McMahon, K.L., McRae, A.F., Nees, F., Papadopoulos Orfanos, D., Paus, T., Poustka, L., Sämann, P.G., Schofield, P.R., Smolka, M.N., Stein, D.J., Strike, L.T., Teeuw, J., Thalamuthu, A., Trollor, J., Walter, H., Wardlaw, J.M., Wen, W., Whelan, R., Apostolova, L.G., Binder, E.B., Boomsma, D.I., Calhoun, V., Crespo-Facorro, B., Deary, I.J., Hulshoff Pol, H., Ophoff, R.A., Pausova, Z., Sachdev, P.S., Saykin, A., Wright, M.J., Thompson, P.M., Schumann, G., and Desrivières, S.
Abstract: DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)—three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.
Published: 2021

45. Plastic modulation of PTSD resting-state networks and subjective wellbeing by EEG neurofeedback

Author: Kluetsch, R. C., Ros, T., Théberge, J., Frewen, P. A., Calhoun, V. D., Schmahl, C., Jetly, R., and Lanius, R. A.
Published: 2014
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46. The impact of parent socio-economic status on executive functioning and cortical morphology in individuals with schizophrenia and healthy controls

Author: Yeo, R. A., Martinez, D., Pommy, J., Ehrlich, S., Schulz, S. C., Ho, B. -C., Bustillo, J. R., and Calhoun, V. D.
Published: 2014

47. Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age

Author: Damaraju, E., Caprihan, A., Lowe, J. R., Allen, E. A., Calhoun, V. D., and Phillips, J. P.
Published: 2014
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48. Joint blind source separation by multiset canonical correlation analysis

Author: Li, Y.-O., Adali, T., Wang, W., and Calhoun, V. D.
Subjects: Correlation (Statistics) -- Usage, Magnetic resonance imaging -- Analysis, Signal processing -- Research, Digital signal processor, Business, Computers, Electronics, Electronics and electrical industries
Published: 2009

49. Using joint ICA to link function and structure using MEG and DTI in schizophrenia

Author: Stephen, J. M., Coffman, B. A., Jung, R. E., Bustillo, J. R., Aine, C. J., and Calhoun, V. D.
Published: 2013
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50. Differential engagement of the fronto-limbic network during emotion processing distinguishes bipolar and borderline personality disorder

Author: Malhi, G S, Tanious, M, Fritz, K, Coulston, C M, Bargh, D M, Phan, K L, Calhoun, V, and Das, P
Published: 2013
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