Author: "Thyreau B" / Search Limiters: Available in Library Collection - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Thyreau B"' showing total 34 results

Start Over Author "Thyreau B" Search Limiters Available in Library Collection

34 results on '"Thyreau B"'

1. 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
Full Text: View/download PDF

2. 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
Full Text: View/download PDF

3. Brain charts for the human lifespan

Author: Armin Raznahan, Eric Courchesne, Andrea Parolin Jackowski, Kamen A. Tsvetanov, Cameron T. Ellis, R.C. Gur, Bin Bae J, Park Mtm, Pedro A. Valdes-Sosa, Simon N. Vandekar, Jacob W. Vogel, Juan Zhou, Machteld Marcelis, Kiho Im, Patricia Ellen Grant, Minhui Ouyang, Blesa Cabez M, Michael V. Lombardo, Sarah E. Morgan, James P. Boardman, Adamson C, Calhoun Vd, Delarue M, James H. Cole, Pichet Binette A, Roberto Toro, David H. Rowitch, Nynke A. Groenewold, Kevin M. Anderson, David T.W. Jones, Michael Schöll, Wang Ys, Aiden Corvin, R.E. Gur, Damien A. Fair, Gareth Ball, Herma Lina Schaare, Andrew Zalesky, Evdokia Anagnostou, Michael J. Meaney, Taki Y, Gareth J. Sullivan, Warrier, Petra E. Vértes, Chixiang Chen, Lisa T. Eyler, Wei Liao, Tomáš Paus, Jeremy A. Elman, Phillip McGuire, Hisham Ziauddeen, William S. Kremen, Etienne Vachon-Presseau, E.T. Bullmore, Christophe Tzourio, White, Hammill Cf, Mothersill D, Richard N. Henson, Jiang Qiu, Duncan E. Astle, Fabrice Crivello, Paul C. Fletcher, Chertavian C, Kim K, Jennifer Crosbie, Russell Schachar, Gabriel A. Devenyi, Manfred G. Kitzbichler, Tianye Jia, Trey Hedden, Sang Jae Lee, Ross D. Markello, Silke Kern, Ian M. Goodyer, Keith A. Johnson, Frauke Beyer, Bernard Mazoyer, A. Heinz, Sylvane Desrivières, Rosenberg, Gary Donohoe, Ong Mq, Alexander D. Edwards, Dan J. Stein, Nenad Medic, Zuo Xn, Travis T. Mallard, Peter Fonagy, Lindsay W. Victoria, Ingmar Skoog, Avram J. Holmes, Jason P. Lerch, Jed T. Elison, Jianfu Li, John H. Gilmore, Rosemary Holt, Caitlin K. Rollins, Carol E. Franz, Pedro Mario Pan, Saashi A Bedford, Yang N, Jonathan C Ipser, Richard A. I. Bethlehem, Tuulari Jj, Stolicyn A, Hua Huang, Bratislav Misic, Conor Liston, Ayub M, Lisa Ronan, Yeo Bt, Sophie Adler, Charles J. Lynch, Faith M. Gunning, Konrad Wagstyl, M. Mallar Chakravarty, John Suckling, Theodore D. Satterthwaite, Bharath Holla, Yap Seng Chong, Jinglei Lv, Jakob Seidlitz, Niall J Bourke, Xinlei Qian, Simon Baron-Cohen, Cynthia M. Ortinau, Deirel Paz Linares, Thyreau B, René S. Kahn, Aaron P. Schultz, Vanessa Cropley, Eric Westman, Mitchell Valdés-Sosa, Rik Ossenkoppele, André Zugman, Hasse Karlsson, Sylvia Villeneuve, Katja Heuer, Di Biase Ma, Margaret L. Westwater, Sofie L. Valk, David J. Sharp, Brigitte Landeau, Matthew Borzage, Kirsten A. Donald, Timothy Rittman, Richard Beare, Giovanni Abrahão Salum, Gunter Schumann, Ryuta Kawashima, Romero-Garcia R, John Blangero, Yun Hj, Russel T. Shinohara, Nicolas Crossley, Simon K. Warfield, Karen Pierce, George S. Alexopoulos, Katharine Dunlop, David C. Glahn, Francois Lalonde, Anqi Qiu, Lana Vasung, Gaël Chételat, Lídice Galán-García, Clifford R. Jack, Reisa A. Sperling, Anna Zettergren, Elizabeth Kelley, Arno Villringer, Andrea Mechelli, Benegal, Aaron Alexander-Bloch, Nicholas B. Turk-Browne, van Amelsvoort T, John D. Lewis, Heather C. Whalley, A. V. Witte, Zdenka Pausova, Joel T. Nigg, Heather J. Zar, Raymond J. Dolan, Christopher D. Smyser, Jay N. Giedd, Lena Palaniyappan, Ali Gholipour, Areces-Gonzalez A, Peter B. Jones, Jacqueline Hoare, Oskar Hansson, Linnea Karlsson, C Pantelis, Paly L, Bonnie Auyeung, Jorge Bosch-Bayard, Bethlehem, Richard [0000-0002-0714-0685], White, Simon [0000-0001-8642-7037], Astle, Duncan [0000-0002-7042-5392], Baron-Cohen, Simon [0000-0001-9217-2544], Henson, Rik [0000-0002-0712-2639], Jones, Peter [0000-0002-0387-880X], Kitzbichler, Manfred [0000-0002-4494-0753], Rittman, Timothy [0000-0003-1063-6937], Rowitch, David [0000-0002-0079-0060], Tsvetanov, Kamen A. [0000-0002-3178-6363], Westwater-Wozniak, Margaret [0000-0002-2918-0979], Ziauddeen, Hisham [0000-0003-4044-1719], Apollo - University of Cambridge Repository, 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, University of Cambridge [UK] (CAM), University of Pennsylvania, Yale University [New Haven], Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Child and Adolescent Psychiatry Department [AP- HP Hôpital Robert Debré], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Département de Neuroscience - Department of Neuroscience, Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Neurology, Amsterdam Neuroscience - Neurodegeneration, 3R-BRAIN, AIBL, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Repository Without Borders Investigators, CALM Team, Cam-CAN, CCNP, COBRE, cVEDA, ENIGMA Developmental Brain Age Working Group, Developing Human Connectome Project, FinnBrain, Harvard Aging Brain Study, IMAGEN, KNE96, The Mayo Clinic Study of Aging, NSPN, POND, The PREVENT-AD Research Group, VETSA, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Auyeung, B.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Baron-Cohen, S.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bedford, S. A.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Holt, R.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Lombardo, M. V.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Seidlitz, J.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Vogel, J. W.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. E.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. C.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Jackowski, A. P.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Chertavian, C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. E.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [White, S. R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Goodyer, I. M.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Henson, R. N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Jones, P. B.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Medic, N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Morgan, S. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Romero-Garcia, R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ronan, L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Suckling, J.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Vertes, P. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Warrier, V.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Westwater, M. L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ziauddeen, H.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Bullmore, E. T.] Univ Cambridge, Dept Psychiat, Cambridge, England, [White, S. R.] Univ Cambridge, MRC Biostat Unit, Cambridge, England, [Vogel, J. W.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Anderson, K. M.] Yale Univ, Dept Psychol, New Haven, CT USA, [Ellis, C. T.] Yale Univ, Dept Psychol, New Haven, CT USA, [Turk-Browne, N. B.] Yale Univ, Dept Psychol, New Haven, CT USA, [Adamson, C.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Ball, G.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Beare, R.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Jackowski, A. P.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Adamson, C.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Beare, R.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Adler, S.] UCL Great Ormond St Inst Child Hlth, London, England, [Alexopoulos, G. S.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Anagnostou, E.] Univ Toronto, Dept Pediat, Toronto, ON, Canada, [Anagnostou, E.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Pierce, K.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Areces-Gonzalez, A.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Paz-Linares, D.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Areces-Gonzalez, A.] Univ Pinar del Rio Hermanos Saiz Montes de Oca, Pinar Del Rio, Cuba, [Astle, D. E.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Henson, R. N.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Whalley, H. C.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Auyeung, B.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Pausova, Z.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Ayub, M.] Queens Univ, Dept Psychiat, Ctr Neurosci Studies, Kingston, ON, Canada, [Ayub, M.] UCL, Mental Hlth Neurosci Res Dept, Div Psychiat, London, England, [Bae, J.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Ball, G.] Univ Melbourne, Dept Paediat, Melbourne, Vic, Australia, [Baron-Cohen, S.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge Lifetime Asperger Syndrome Serv CLASS, Cambridge, England, [Benegal, V.] Natl Inst Mental Hlth & Neurosci NIMHANS, Ctr Addict Med, Bengaluru, India, [Beyer, F.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Villringer, A.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Witte, A. V.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Blangero, J.] Univ Texas Rio Grande Valley, South Texas Diabet & Obes Inst, Dept Human Genet, Edinburg, TX USA, [Blesa Cabez, M.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Boardman, J. P.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Sullivan, G.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Borzage, M.] Univ Southern Calif, Childrens Hosp Los Angeles, Keck Sch Med, Fetal & Neonatal Inst,Div Neonatol,Dept Pediat, Los Angeles, CA 90007 USA, [Bosch-Bayard, J. F.] Montreal Neurol Inst, Ludmer Ctr Neuroinformat & Mental Hlth, McGill Ctr Integrat Neurosci, Montreal, PQ, Canada, [Bosch-Bayard, J. F.] McGill Univ, Montreal, PQ, Canada, [Chakravarty, M. M.] McGill Univ, Montreal, PQ, Canada, [Bourke, N.] Imperial Coll London, Dept Brain Sci, London, England, [Sharp, D.] Imperial Coll London, Dept Brain Sci, London, England, [Alexander-Bloch, A. F.] Imperial Coll London, Dept Brain Sci, London, England, [Bourke, N.] Dementia Res Inst, Care Res & Technol Ctr, London, England, [Calhoun, V. D.] Georgia State Univ, Triinst Ctr Translat Res Neuroimaging & Data Sci, Georgia Inst Technol, Atlanta, GA 30303 USA, [Calhoun, V. D.] Emory Univ, Atlanta, GA 30322 USA, [Chakravarty, M. M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Comp Brain Anat CoBrA Lab, Montreal, PQ, Canada, [Chen, C.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Shinohara, R. T.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Chetelat, G.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Delarue, M.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Landeau, B.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Paly, L.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Chong, Y. S.] Agcy Sci Technol & Res, Singapore Inst Clin Sci, Singapore, Singapore, [Chong, Y. S.] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Obstet & Gynaecol, Singapore, Singapore, [Cole, J. H.] UCL, Ctr Med Image Comp CMIC, London, England, [Cole, J. H.] UCL, Dementia Res Ctr DRC, London, England, [Corvin, A.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Costantino, M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Verdun, PQ, Canada, [Costantino, M.] McGill Univ, Undergrad Program Neurosci, Montreal, PQ, Canada, [Courchesne, E.] Univ Calif San Diego, Dept Neurosci, San Diego, CA 92103 USA, [Courchesne, E.] Univ Calif San Diego, Autism Ctr Excellence, San Diego, CA 92103 USA, [Crivello, F.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Mazoyer, B.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Cropley, V. L.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Di Biase, M. A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Lv, J.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Zalesky, A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Hammill, C. F.] Hosp Sick Children, Toronto, ON, Canada, [Schachar, R. J.] Hosp Sick Children, Toronto, ON, Canada, [Crossley, N.] Pontificia Univ Catolica Chile, Sch Med, Dept Psychiat, Santiago, Chile, [Crossley, N.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [McGuire, P.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [Crossley, N.] Inst Milenio Intelligent Healthcare Engn, Santiago, Chile, [Delorme, R.] Robert Debre Univ Hosp, AP HP, Child & Adolescent Psychiat Dept, Paris, France, [Delorme, R.] Inst Pasteur, Human Genet & Cognit Funct, Paris, France, [Desrivieres, S.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Social Genet & Dev Psychiat Ctr, London, England, [Devenyi, G. A.] Douglas Mental Hlth Univ Inst, McGill Dept Psychiat, Cerebral Imaging Ctr, Montreal, PQ, Canada, [Devenyi, G. A.] McGill Univ, Dept Psychiat, Montreal, PQ, Canada, [Di Biase, M. A.] Harvard Med Sch, Brigham & Womens Hosp, Dept Psychiat, Boston, MA 02115 USA, [Dolan, R.] UCL, Max Planck UCL Ctr Computat Psychiat & Ageing Res, London, England, [Dolan, R.] Wellcome Ctr Human Neuroimaging, London, England, [Wagstyl, K.] Wellcome Ctr Human Neuroimaging, London, England, [Donald, K. A.] Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Div Dev Paediat, Cape Town, South Africa, [Donald, K. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Groenewold, N. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Donohoe, G.] Natl Univ Ireland Galway, Sch Psychol, Ctr Neuroimaging Cognit & Genom NICOG, Galway, Ireland, [Dunlop, K.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Lynch, C.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Edwards, A. D.] Kings Coll London, Ctr Dev Brain, London, England, [Edwards, A. D.] Evelina London Childrens Hosp, London, England, [Edwards, A. D.] MRC Ctr Neurodev Disorders, London, England, [Elison, J. T.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Fair, D. A.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Feczko, E.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Ellis, C. T.] Haskins Labs Inc, New Haven, CT USA, [Elman, J. A.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Franz, C. E.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Kremen, W. S.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Eyler, L.] VA San Diego Healthcare, Desert Pacific Mental Illness Res Educ & Clin Ctr, San Diego, CA USA, [Eyler, L.] Univ Calif San Diego, Dept Psychiat, Los Angeles, CA USA, [Fletcher, P. C.] Univ Cambridge, Dept Psychiat, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Wellcome Trust MRC Inst Metab Sci, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Jones, P. B.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Suckling, J.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Ziauddeen, H.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Fonagy, P.] UCL, Dept Clin Educ & Hlth Psychol, London, England, [Fonagy, P.] Anna Freud Natl Ctr Children & Families, London, England, [Galan-Garcia, L.] Cuban Ctr Neurosci, Havana, Cuba, [Valdes-Sosa, M. J.] Cuban Ctr Neurosci, Havana, Cuba, [Gholipour, A.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Warfield, S. K.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Giedd, J.] Univ Calif San Diego, Dept Child & Adolescent Psychiat, San Diego, CA 92103 USA, [Giedd, J.] Univ Calif San Diego, Dept Psychiat, San Diego, CA 92103 USA, [Gilmore, J. H.] Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27515 USA, [Glahn, D. C.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Im, K.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Mathias, S. R.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Rodrigue, A.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Glahn, D. C.] Harvard Med Sch, Boston, MA 02115 USA, [Im, K.] Harvard Med Sch, Boston, MA 02115 USA, [Johnson, K. A.] Harvard Med Sch, Boston, MA 02115 USA, [Mathias, S. R.] Harvard Med Sch, Boston, MA 02115 USA, [Rodrigue, A.] Harvard Med Sch, Boston, MA 02115 USA, [Schultz, A. P.] Harvard Med Sch, Boston, MA 02115 USA, [Sperling, R. A.] Harvard Med Sch, Boston, MA 02115 USA, [Grant, P. E.] Harvard Med Sch, Fetal Neonatal Neuroimaging & Dev Sci Ctr, Boston Childrens Hosp, Div Newborn Med & Neuroradiol, Boston, MA 02115 USA, [Groenewold, N. A.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Zar, H. J.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Gunning, F. M.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Victoria, L. W.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Hammill, C. F.] Mouse Imaging Ctr, Toronto, ON, Canada, [Hansson, O.] Lund Univ, Dept Clin Sci Malmo, Clin Memory Res Unit, Malmo, Sweden, [Hansson, O.] Skane Univ Hosp, Memory Clin, Malmo, Sweden, [Hedden, T.] Icahn Sch Med Mt Sinai, Dept Neurol, New York, NY 10029 USA, [Hedden, T.] Harvard Med Sch, Massachusetts Gen Hosp, Dept Radiol, Athinoula Martinos Ctr Biomed Imaging, Boston, MA 02115 USA, [Heinz, A.] Charite Univ Med Berlin, Charite Campus Mitte, Berlin, Germany, [Heinz, A.] Free Univ Berlin, Charite Campus Mitte, Berlin, Germany, [Heinz, A.] Humboldt Univ, Dept Psychiat & Psychotherapy, Charite Campus Mitte, Berlin, Germany, [Heuer, K.] Max Planck Inst Human Cognit & Brain Sci, Dept Neuropsychol, Leipzig, Germany, [Heuer, K.] Univ Paris, Paris, France, [Toro, R.] Univ Paris, Paris, France, [Hoare, J.] Univ Cape Town, Dept Psychiat, Cape Town, South Africa, [Holla, B.] NIMHANS, Dept Integrat Med, Bengaluru, India, [Holla, B.] NIMHANS, Dept Psychiat, Accelerator Program Discovery Brain Disorders Usi, Bengaluru, India, [Holmes, A. J.] Yale Univ, Dept Psychol, New Haven, CT USA, [Villeneuve, S.] Yale Univ, Dept Psychol, New Haven, CT USA, [Holmes, A. J.] Yale Univ, Dept Psychiat, New Haven, CT 06520 USA, [Villeneuve, S.] Yale Univ, Dept Psychiat, New Haven, CT 06520 USA, [Huang, H.] Childrens Hosp Philadelphia, Radiol Res, Philadelphia, PA 19104 USA, [Ouyang, M.] Childrens Hosp Philadelphia, Radiol Res, Philadelphia, PA 19104 USA, [Huang, H.] Univ Penn, Dept Radiol, Perelman Sch Med, Philadelphia, PA 19104 USA, [Ipser, J.] Univ Cape Town, Dept Psychiat & Mental Hlth, Clin Neurosci Inst, Cape Town, South Africa, [Jack, C. R., Jr.] Mayo Clin, Dept Radiol, Rochester, MN USA, [Jones, D. T.] Mayo Clin, Dept Radiol, Rochester, MN USA, Univ Fed Sao Paulo, Dept Psychiat, Sao Paulo, Brazil, [Jackowski, A. P.] Natl Inst Dev Psychiat, Beijing, Peoples R China, [Jia, T.] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Shanghai, Peoples R China, [Jia, T.] Fudan Univ, Minist Educ, Key Lab Computat Neurosci & Brain Inspired Intell, Shanghai, Peoples R China, [Jia, T.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Ctr Populat Neurosci & Precis Med PONS, SGDP Ctr, London, England, [Johnson, K. A.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Schultz, A. P.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Sperling, R. A.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Johnson, K. A.] Brigham & Womens Hosp, Dept Neurol, Ctr Alzheimer Res & Treatment, 75 Francis St, Boston, MA 02115 USA, [Sperling, R. A.] Brigham & Womens Hosp, Dept Neurol, Ctr Alzheimer Res & Treatment, 75 Francis St, Boston, MA 02115 USA, [Johnson, K. A.] Massachusetts Gen Hosp, Dept Radiol, Boston, MA USA, [Jones, D. T.] Mayo Clin, Dept Neurol, Rochester, MN USA, [3R-BRAIN] Mayo Clin, Dept Neurol, Rochester, MN USA, [Kahn, R. S.] Icahn Sch Med Mt Sinai, Dept Psychiat, New York, NY 10029 USA, [Karlsson, H.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Karlsson, L.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Tuulari, J. J.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Karlsson, H.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Karlsson, L.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Tuulari, J. J.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Karlsson, H.] Turku Univ Hosp, Turku, Finland, [Karlsson, L.] Turku Univ Hosp, Turku, Finland, [Tuulari, J. J.] Turku Univ Hosp, Turku, Finland, [Karlsson, H.] Turku Univ Hosp, Ctr Populat Hlth Res, Turku, Finland, [Karlsson, L.] Turku Univ Hosp, Ctr Populat Hlth Res, Turku, Finland, [Karlsson, H.] Univ Turku, Turku, Finland, [Karlsson, L.] Univ Turku, Turku, Finland, [Kawashima, R.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Taki, Y.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Thyreau, B.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Kelley, E. A.] Queens Univ, Ctr Neurosci Studies, Dept Psychol, Kingston, ON, Canada, [Kelley, E. A.] Queens Univ, Ctr Neurosci Studies, Dept Psychiat, Kingston, ON, Canada, [Kern, S.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Skoog, I.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Zettergren, A.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Kern, S.] Sahlgrens Univ Hosp, Psychiat Cognit & Old Age Psychiat Clin, Reg Vastra Gotaland, Gothenburg, Sweden, [Skoog, I.] Sahlgrens Univ Hosp, Psychiat Cognit & Old Age Psychiat Clin, Reg Vastra Gotaland, Gothenburg, Sweden, [Kim, K. W.] Seoul Natl Univ, Dept Brain & Cognit Sci, Coll Nat Sci, Seoul, South Korea, [Kim, K. W.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Kim, K. W.] Seoul Natl Univ, Dept Psychiat, Coll Med, Seoul, South Korea, [Kim, K. W.] SNU MRC, Inst Human Behav Med, Seoul, South Korea, [Lalonde, F.] NIMH, Sect Dev Neurogenom, Human Genet Branch, Bethesda, MD 20892 USA, [Raznahan, A.] NIMH, Sect Dev Neurogenom, Human Genet Branch, Bethesda, MD 20892 USA, [Lee, S.] Seoul Natl Univ, Coll Nat Sci, Dept Brain & Cognit Sci, Seoul, South Korea, [Lerch, J.] Univ Toronto, Dept Med Biophys, Toronto, ON, Canada, [Lerch, J.] Univ Oxford, Nuffield Dept Clin Neurosci, FMRIB, Wellcome Ctr Integrat Neuroimaging, Oxford, England, [Lewis, J. D.] McGill Univ, Montreal Neurol Inst, Montreal, PQ, Canada, [Li, J.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Liao, W.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Valdes-Sosa, P. A.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Liston, C.] Weill Cornell Med, Dept Psychiat, New York, NY USA, [Liston, C.] Weill Cornell Med, Brain & Mind Res Inst, New York, NY USA, [Lombardo, M. V.] Ist Italiano Tecnol, Ctr Neurosci & Cognit Syst UniTn, Lab Autism & Neurodev Disorders, Rovereto, Italy, [Lv, J.] Univ Sydney, Sch Biomed Engn, Sydney, NSW, Australia, [Lv, J.] Univ Sydney, Brain & Mind Ctr, Sydney, NSW, Australia, [Mallard, T. T.] Univ Texas Austin, Dept Psychol, Austin, TX 78712 USA, [Marcelis, M.] Maastricht Univ, Sch Mental Hlth & Neurosci, Dept Psychiat & Neuropsychol, EURON,Med Ctr, Maastricht, Netherlands, [Marcelis, M.] Inst Mental Hlth Care Eindhoven GGzE, Eindhoven, Netherlands, [Markello, R. D.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Misic, B.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Vasung, L.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Mazoyer, B.] Douglas Mental Hlth Univ Inst, Ludmer Ctr Neuroinformat & Mental Hlth, Montreal, PQ, Canada, [Meaney, M. J.] Douglas Mental Hlth Univ Inst, Ludmer Ctr Neuroinformat & Mental Hlth, Montreal, PQ, Canada, [Meaney, M. J.] Singapore Inst Clin Sci, Singapore, Singapore, [Mechelli, A.] Bordeaux Univ Hosp, Bordeaux, France, [Morgan, S. E.] Univ Cambridge, Dept Comp Sci & Technol, Cambridge, England, [Morgan, S. E.] Alan Turing Inst, London, England, [Vertes, P. E.] Alan Turing Inst, London, England, [Mothersill, D.] Natl Coll Ireland, Sch Business, Dept Psychol, Dublin, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Sch Psychol, Galway, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Ctr Neuroimaging & Cognit Genom, Galway, Ireland, [Mothersill, D.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Nigg, J.] Oregon Hlth & Sci Univ, Dept Psychiat, Sch Med, Portland, OR 97201 USA, [Ong, M. Q. W.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Qian, X.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Ortinau, C.] Washington Univ, Dept Pediat, St Louis, MO 63130 USA, [Ossenkoppele, R.] Vrije Univ Amsterdam, Alzheimer Ctr Amsterdam, Amsterdam UMC, Dept Neurol,Amsterdam Neurosci, Amsterdam, Netherlands, [Ossenkoppele, R.] Lund Univ, Clin Memory Res Unit, Lund, Sweden, [Palaniyappan, L.] Univ Western Ontario, Robarts Res Inst, London, ON, Canada, [Palaniyappan, L.] Univ Western Ontario, Brain & Mind Inst, London, ON, Canada, [Pan, P. M.] Fed Univ Sao Poalo UNIFESP, Dept Psychiat, Sao Poalo, Brazil, [Pan, P. M.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Zugman, A.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Pantelis, C.] Univ Melbourne, Dept Psychiat, Melbourne Neuropsychiat Ctr, Carlton, Vic, Australia, [Pantelis, C.] Melbourne Hlth, Carlton, Vic, Australia, [Pantelis, C.] Univ Melbourne, Melbourne Sch Engn, Parkville, Vic, Australia, [Pantelis, C.] Florey Inst Neurosci & Mental Hlth, Parkville, Vic, Australia, [Park, M. M.] Western Univ, Schulich Sch Med & Dent, Dept Psychiat, London, ON, Canada, [Rollins, C. K.] Univ Montreal, Dept Psychiat, Fac Med, Montreal, PQ, Canada, [Rollins, C. K.] Univ Montreal, CHU St Justine, Montreal, PQ, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychiat, Toronto, ON, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Physiol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Nutr Sci, Toronto, ON, Canada, [Paz-Linares, D.] Cuban Neurosci Ctr, Havana, Cuba, [Pichet Binette, A.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Villeneuve, S.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Pichet Binette, A.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Villeneuve, S.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Qiu, J.] Southwest Univ, Sch Psychol, Chongqing, Peoples R China, [Qiu, A.] Natl Univ Singapore, N1 Inst Hlth, Dept Biomed Engn, Singapore, Singapore, [Rittman, T.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Tsvetanov, K. A.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Rollins, C. K.] Harvard Med Sch, Dept Neurol, Boston, MA 02115 USA, [Rollins, C. K.] Boston Childrens Hosp, Dept Neurol, Boston, MA USA, [Romero-Garcia, R.] Univ Seville, Dpto Fisiol Med & Biofis, Inst Biomed Sevilla IBiS HUVR CSIC, Seville, Spain, [Rosenberg, M. D.] Univ Chicago, Dept Psychol, 5848 S Univ Ave, Chicago, IL 60637 USA, [Rosenberg, M. D.] Univ Chicago, Inst Neurosci, Chicago, IL USA, [Rowitch, D. H.] Univ Cambridge, Dept Paediat, Cambridge, England, [Rowitch, D. H.] Univ Cambridge, Wellcome MRC Cambridge Stem Cell Inst, Cambridge, England, [Salum, G. A.] Univ Fed Rio Grande Sul UFRGS, Hosp Clin Porto Alegre, Dept Psychiat, Porto Alegre, RS, Brazil, [Salum, G. A.] Natl Inst Dev Psychiat INPD, Sao Paulo, Brazil, [Schaare, H. L.] Max Planck Inst Human Cognit & Brain Sci, Otto Hahn Grp Cognit Neurogenet, Leipzig, Germany, [Schaare, H. L.] Res Ctr Juelich, Inst Neurosci & Med INM 7 Brain & Behav, Julich, Germany, [Schultz, A. P.] Massachusetts Gen Hosp, Dept Radiol, Athinoula Martinos Ctr Biomed Imaging, Charlestown, MA USA, [Schumann, G.] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Ctr Populat Neurosci & Stratified Med PONS, Shanghai, Peoples R China, [Schumann, G.] Charite Campus Mitte, Dept Psychiat & Psychotherapy, Charite Mental Hlth, PONS Ctr, Berlin, Germany, [Scholl, M.] Univ Gothenburg, Wallenberg Ctr Mol & Translat Med, Gothenburg, Sweden, [Scholl, M.] Univ Gothenburg, Dept Psychiat & Neurochem, Gothenburg, Sweden, [Scholl, M.] UCL, Queens Sq Inst Neurol, Dementia Res Ctr, London, England, [Sharp, D.] UK Dementia Res Inst, Care Res & Technol Ctr, London, England, [Shinohara, R. T.] Univ Penn, Perelman Sch Med, Dept Radiol, Ctr Biomed Image Comp & Analyt, Philadelphia, PA 19104 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Neurol, St Louis, MO 63110 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Pediat, St Louis, MO 63110 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Radiol, St Louis, MO 63110 USA, [Stein, D. J.] Univ Cape Town, Dept Psychiat, SA MRC Unit Risk & Resilience Mental Disorders, Cape Town, South Africa, [Stein, D. J.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Stolicyn, A.] Univ Edinburgh, Ctr Clin Brain Sci, Div Psychiat, Edinburgh, Midlothian, Scotland, [Whalley, H. C.] Univ Edinburgh, Ctr Clin Brain Sci, Div Psychiat, Edinburgh, Midlothian, Scotland, [Toro, R.] Inst Pasteur, Dept Neurosci, Paris, France, [Traut, N.] Inst Pasteur, Dept Neurosci, Paris, France, [Traut, N.] Univ Paris 05, Ctr Res & Interdisciplinar CRI, Paris, France, [Tsvetanov, K. A.] Univ Cambridge, Dept Psychol, Cambridge, England, [Turk-Browne, N. B.] Yale Univ, Wu Tsai Inst, New Haven, CT USA, [Tuulari, J. J.] Univ Turku, Dept Clin Med, Turku, Finland, [Tuulari, J. J.] Univ Turku, Turku Coll Sci Med & Technol, Turku, Finland, [Tzourio, C.] Univ Bordeaux, Bordeaux Populat Hlth Res Ctr, CHU Bordeaux, U1219,INSERM, Bordeaux, France, [Vachon-Presseau, E.] McGill Univ, Fac Dent Med & Oral Hlth Sci, Montreal, PQ, Canada, [Valdes-Sosa, P. A.] McGill Univ, Alan Edwards Ctr Res Pain AECRP, Montreal, PQ, Canada, [Valk, S. L.] Forschungszentrum Julich, Inst Neurosci & Med 7, Julich, Germany, [Valk, S. L.] Max Planck Inst Human Cognit & Brain Sci, Leipzig, Germany, [van Amelsvoort, T.] Maastricht Univ, Dept Psychiat & Neurosychol, Maastricht, Netherlands, [Vandekar, S. N.] Vanderbilt Univ, Dept Biostat, 221 Kirkland Hall, Nashville, TN 37235 USA, [Villeneuve, S.] Vanderbilt Univ, Med Ctr, Dept Biostat, Nashville, TN USA, [Villringer, A.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Witte, A. V.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Zuo, X. N.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Wang, Y. S.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yeo, B.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Wang, Y. S.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Wang, Y. S.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Yang, N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Zuo, X. N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Wang, Y. S.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Yang, N.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Westman, E.] Karolinska Inst, Ctr Alzheimer Res, Dept Neurobiol Care Sci & Soc, Div Clin Geriatr, Stockholm, Sweden, [Witte, A. V.] Univ Leipzig, CRC 1052 Obes Mech, Fac Med, Leipzig, Germany, [Zhou, J. H.] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat MR Res, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, N1 Inst Hlth, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Inst Digital Med, Singapore, Singapore, [Yun, H.] Natl Univ Singapore, Integrat Sci & Engn Programme ISEP, Singapore, Singapore, [Zar, H. J.] Univ Melbourne, Dept Biomed Engn, Melbourne, Vic, Australia, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat Magnet Resonance Res, Singapore, Singapore, [Ziauddeen, H.] Univ Cambridge, Wellcome Trust MRC Inst Metab Sci, Cambridge, England, [Zugman, A.] NIMH, NIH, Bethesda, MD 20892 USA, [Zugman, A.] Escola Paulista Med, Dept Psychiat, Sao Paulo, Brazil, [Zuo, X. N.] Nanning Normal Univ, Sch Educ Sci, Key Lab Brain & Educ, Nanning, Peoples R China, British Academy Postdoctoral fellowship, NIMH, UKRI Medical Research Council, NIHR Cambridge Biomedical Research Centre, NIHR Senior Investigator award, MRC research infrastructure award, Commonwealth Scientific and Industrial Research Organisation (CSIRO), and Ontario Brain Institute
Subjects: 631/378/2649, OpenPain Project, KNE96, Growth, Psychiatric-disorders, DISEASE, 3R-BRAIN, Brain charts, MRI Brain, OASIS-3, Disease, CCNP, 631/378/2571, UMN BCP, Multidisciplinary, medicine.diagnostic_test, PSYCHIATRIC-DISORDERS, article, Brain, Human brain, ASSOCIATION, Magnetic Resonance Imaging, Harvard Aging Brain Study, The Mayo Clinic Study of Aging, NSPN, medicine.anatomical_structure, GROWTH, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], ddc:500, BURDEN, WHITE-MATTER, FinnBrain, Harvard Aging Brain Study, Organization, Mri, MRI, medicine.medical_specialty, Concurrent validity, MODELS, Cam-CAN, Longevity, CALM Team, POND, Neuroimaging, Burden, ORGANIZATION, AIBL, The PREVENT-AD Research Group, VETSA, Cortical thickness, Association, Physical medicine and rehabilitation, FinnBrain, IMAGEN, KNE96, White-matter, medicine, Humans, ASRB, 631/378/1689, COBRE, business.industry, 631/378/2611, Brain morphometry, Neurosciences, Alzheimer’s Disease Repository Without Borders Investigators, Magnetic resonance imaging, Alzheimer’s Disease Neuroimaging Initiative, Anthropometry, Body Height, Brain growth, Birth, 59/57, Normative, IMAGEN, ENIGMA Developmental Brain Age working group, NSPN, business, CCNP, 3R-BRAIN, CORTICAL THICKNESS, Developing Human Connectome Project, ENIGMA Developmental Brain Age working group, The PREVENT-AD Research Group, VETSA, Bullmore, E.T
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., R.A.I.B. was supported by a British Academy Postdoctoral fellowship and by the Autism Research Trust. J. Seidlitz was supported by NIMH T32MH019112-29 and K08MH120564. S.R.W. was funded by UKRI Medical Research Council MC_UU_00002/2 and was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network. A.F.A.-B. was supported by NIMH K08MH120564. Data were curated and analysed using a computational facility funded by an MRC research infrastructure award (MR/M009041/1) to the School of Clinical Medicine, University of Cambridge and supported by the mental health theme of the NIHR Cambridge Biomedical Research Centre.
Published: 2022

4. Brain charts for the human lifespan

Author: Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, 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, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, Alexander-Bloch, AF, Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, 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, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, and Alexander-Bloch, AF
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

5. Brain charts for the human lifespan (vol 604, pg 525, 2022)

Author: Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, 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, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, Alexander-Bloch, AF, Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, 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, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, and Alexander-Bloch, AF
Published: 2022

6. 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

7. Identification of common variants associated with human hippocampal and intracranial volumes

Author: Stein, Jason L, Medland, Sarah E, Bernard, Manon, Nauck, Matthias, Nöthen, Markus M., Olvera, Rene L, Pandolfo, Massimo, Pike, G Bruce, Puls, Ralf, Reinvang, Ivar, Rentería, Miguel E, Rietschel, Marcella, Roffman, Joshua L, Brown, Andrew A, Royle, Natalie A, Rujescu, Dan, Savitz, Jonathan, Schnack, Hugo G, Schnell, Knut, Seiferth, Nina, Smith, Colin, Steen, Vidar M, Valdés Hernández, Maria C, Van den Heuvel, Martijn, Cannon, Dara M, van der Wee, Nic J, Van Haren, Neeltje E M, Veltman, Joris A, Völzke, Henry, Walker, Robert, Westlye, Lars T, Whelan, Christopher D, Agartz, Ingrid, Boomsma, Dorret I, Cavalleri, Gianpiero L, Chakravarty, M Mallar, Dale, Anders M, Djurovic, Srdjan, Drevets, Wayne C, Hagoort, Peter, Hall, Jeremy, Heinz, Andreas, Jack, Clifford R, Foroud, Tatiana M, Le Hellard, Stephanie, Macciardi, Fabio, Christoforou, Andrea, Montgomery, Grant W, Poline, Jean Baptiste, Porteous, David J, Sisodiya, Sanjay M, Starr, John M, Sussmann, Jessika, Toga, Arthur W, Veltman, Dick J, Walter, Henrik, Weiner, Michael W, Domin, Martin, Initiative, Alzheimer's Disease Neuroimaging, Consortium, EPIGEN, Consortium, IMAGEN, Group, Saguenay Youth Study, Bis, Joshua C, Ikram, M Arfan, Smith, Albert V, Gudnason, Vilmundur, Tzourio, Christophe, Vernooij, Meike W, Grimm, Oliver, Launer, Lenore J, DeCarli, Charles, Seshadri, Sudha, Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology, Andreassen, Ole A, Apostolova, Liana G, Bastin, Mark E, Blangero, John, Brunner, Han G, Buckner, Randy L, Hollinshead, Marisa, Cichon, Sven, Coppola, Giovanni, de Zubicaray, Greig I, Deary, Ian J, Donohoe, Gary, de Geus, Eco J C, Espeseth, Thomas, Fernández, Guillén, Glahn, David C, Grabe, Hans J, Holmes, Avram J, Hardy, John, Hulshoff Pol, Hilleke E, Jenkinson, Mark, Kahn, René S, McDonald, Colm, McIntosh, Andrew M, McMahon, Francis J, McMahon, Katie L, Meyer-Lindenberg, Andreas, Morris, Derek W, Homuth, Georg, Müller-Myhsok, Bertram, Nichols, Thomas E, Ophoff, Roel A, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda W, Potkin, Steven G, Sämann, Philipp G, Saykin, Andrew J, Schumann, Gunter, Vasquez, Alejandro Arias, Hottenga, Jouke-Jan, Smoller, Jordan W, Wardlaw, Joanna M, Weale, Michael E, Martin, Nicholas G, Franke, Barbara, Wright, Margaret J, Thompson, Paul M, Consortium, Enhancing Neuro Imaging Genetics through Meta-Analysis, Weiner, Michael, Aisen, Paul, Langan, Camilla, Petersen, Ronald, Jagust, William, Trojanowki, John Q, Beckett, Laurel, Green, Robert C, Morris, John, Liu, Enchi, Lopez, Lorna M, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Hansell, Narelle K, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Hwang, Kristy S, Thompson, Paul, Schuff, Norbert, Alexander, Gene, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Kim, Sungeun, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, J. Q., Shaw, Les, Lee, Virginia M Y, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Laje, Gonzalo, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lee, Phil H, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Liu, Xinmin, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Carroll, Maria, Loth, Eva, Leon, Sue, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, Mitsis, Effie, Romirowsky, Aliza, deToledo-Morrell, Leyla, Hibar, Derrek P, Lourdusamy, Anbarasu, Shah, Raj C, Duara, Ranjan, Varon, Daniel, Roberts, Peggy, Albert, Marilyn, Onyike, Chiadi, Kielb, Stephanie, Rusinek, Henry, de Leon, Mony J, Glodzik, Lidia, Mattingsdal, Morten, De Santi, Susan, Doraiswamy, P Murali, Petrella, Jeffrey R, Coleman, R Edward, Arnold, Steven E, Karlawish, Jason H, Wolk, David, Smith, Charles D, Jicha, Greg, Hardy, Peter, Mohnke, Sebastian, Lopez, Oscar L, Oakley, MaryAnn, Simpson, Donna M, Porsteinsson, Anton P, Goldstein, Bonnie S, Martin, Kim, Makino, Kelly M, Ismail, M Saleem, Mulnard, Ruth A, Thai, Gaby, Maniega, Susana Muñoz, Mc-Adams-Ortiz, Catherine, Womack, Kyle, Mathews, Dana, Quiceno, Mary, Diaz-Arrastia, Ramon, King, Richard, Weiner, Myron, Martin-Cook, Kristen, DeVous, Michael, Levey, Allan I, Nho, Kwangsik, Lah, James J, Cellar, Janet S, Burns, Jeffrey M, Anderson, Heather S, Swerdlow, Russell H, Apostolova, Liana, Lu, Po H, Bartzokis, George, Silverman, Daniel H S, Graff-Radford, Neill R, Nugent, Allison C, Parfitt, Francine, Johnson, Heather, Farlow, Martin R, Hake, Ann Marie, Matthews, Brandy R, Herring, Scott, van Dyck, Christopher H, Carson, Richard E, MacAvoy, Martha G, Chertkow, Howard, O'Brien, Carol, Bergman, Howard, Hosei, Chris, Black, Sandra, Stefanovic, Bojana, Caldwell, Curtis, Hsiung, Ging-Yuek Robin, Feldman, Howard, Mudge, Benita, Assaly, Michele, Kertesz, Andrew, Papmeyer, Martina, Rogers, John, Trost, Dick, Bernick, Charles, Munic, Donna, Kerwin, Diana, Mesulam, Marek-Marsel, Lipowski, Kristina, Wu, Chuang-Kuo, Johnson, Nancy, Sadowsky, Carl, Pütz, Benno, Martinez, Walter, Villena, Teresa, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, Sperling, Reisa A, Johnson, Keith A, Marshall, Gad, Frey, Meghan, Yesavage, Jerome, Ramasamy, Adaikalavan, Taylor, Joy L, Lane, Barton, Rosen, Allyson, Tinklenberg, Jared, Sabbagh, Marwan, Belden, Christine, Jacobson, Sandra, Kowall, Neil, Killiany, Ronald, Budson, Andrew E, Senstad, Rudy E, Rasmussen, Jerod, Norbash, Alexander, Johnson, Patricia Lynn, Obisesan, Thomas O, Wolday, Saba, Bwayo, Salome K, Lerner, Alan, Hudson, Leon, Ogrocki, Paula, Fletcher, Evan, Carmichael, Owen, Rijpkema, Mark, Olichney, John, Kittur, Smita, Borrie, Michael, Lee, T-Y, Bartha, Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M, Risacher, Shannon L, Preda, Adrian, Nguyen, Dana, Tariot, Pierre, Fleisher, Adam, Reeder, Stephanie, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Scharre, Douglas W, Kataki, Maria, Roddey, J Cooper, Zimmerman, Earl A, Celmins, Dzintra, Brown, Alice D, Pearlson, Godfrey D, Blank, Karen, Anderson, Karen, Santulli, Robert B, Schwartz, Eben S, Sink, Kaycee M, Rose, Emma J, Williamson, Jeff D, Garg, Pradeep, Watkins, Franklin, Ott, Brian R, Querfurth, Henry, Tremont, Geoffrey, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Rosen, Howard J, Ryten, Mina, Miller, Bruce L, Mintzer, Jacobo, Longmire, Crystal Flynn, Spicer, Kenneth, Finger, Elizabeth, Rachinsky, Irina, Drost, Dick, Cavalleri, Gianpiero, Alhusaini, Saud, Delanty, Norman, Whelan, Christopher, Sisodiya, Sanjay, Kasperaviciute, Dalia, Matarin, Mar, Depondt, Chantal, Goldstein, David B, Heinzen, Erin L, Shianna, Kevin, Sprooten, Emma, Radtke, Rodney, Ottmann, Ruth, Sergievsky, G. H., Schumann, G., Conrod, P., Reed, L., Barker, G., Williams, S., Loth, E., Struve, M., Strengman, Eric, Lourdusamy, A., Cattrell, A., Nymberg, C., Topper, L., Smith, L., Havatzias, S., Stueber, K., Mallik, C., Stacey, D., Wong, C Peng, Teumer, Alexander, Werts, H., Andrew, C., Desrivieres, S., Heinz, A., Gallinat, J., Häke, I., Ivanov, N., Klär, A., Reuter, J., Winkler, Anderson M, Trabzuni, Daniah, Palafox, C., Hohmann, C., Schilling, C., Lüdemann, K., Romanowski, A., Ströhle, A., Wolff, E., Rapp, M., Ittermann, B., Brühl, R., Turner, Jessica, Ihlenfeld, A., Walaszek, B., Schubert, F., Garavan, H., Connolly, C., Jones, J., Lalor, E., McCabe, E., Ní Shiothcháin, A., Whelan, R., van Eijk, Kristel, Spanagel, R., Leonardi-Essmann, F., Sommer, W., Flor, H., Vollstaedt-Klein, S., Nees, F., Banaschewski, T., Poustka, L., Steiner, S., Mann, K., van Erp, Theo G M, Buehler, M., Rietschel, M., Stolzenburg, E., Schmal, C., Schirmbeck, F., Paus, T., Gowland, P., Heym, N., Lawrence, C., Newman, C., van Tol, Marie-Jose, Pausova, Z., Smolka, M., Huebner, T., Ripke, S., Mennigen, E., Muller, K., Ziesch, V., Büchel, C., Bromberg, U., Fadai, T., Wittfeld, Katharina, Lueken, L., Yacubian, J., Finsterbusch, J., Martinot, J. L., Artiges, E., Bordas, N., de Bournonville, S., Bricaud, Z., Gollier Briand, F., Lemaitre, H., Wolf, Christiane, Massicotte, J., Miranda, R., Paillère Martinot, M. L., Penttilä, J., Poline, J. B., Barbot, A., Schwartz, Y., Lalanne, C., Frouin, V., Thyreau, B., Woudstra, Saskia, Dalley, J., Mar, A., Robbins, T., Subramaniam, N., Theobald, D., Richmond, N., de Rover, M., Molander, A., Jordan, E., Robinson, E., Aleman, Andre, Hipolata, L., Moreno, M., Arroyo, M., Stephens, D., Ripley, T., Crombag, H., Pena, Y., Lathrop, M., Zelenika, D., Heath, S., Lanzerath, D., Heinrichs, B., Spranger, T., Fuchs, B., Speiser, C., Resch, F., Haffner, J., Parzer, P., Brunner, R., Klaassen, A., Toro, Roberto, Almasy, Laura, Klaassen, I., Constant, P., Mignon, X., Thomsen, T., Zysset, S., Vestboe, A., Ireland, J., Rogers, J., Binder, Elisabeth B, Chakravarty, Mallar, Smith, Albert Vernon, van der Lijn, Fedde, Crivello, Fabrice, Fornage, Myriam, Shulman, Joshua M, Brohawn, David G, Schmidt, Helena, Srikanth, Velandai, Schuur, Maaike, Yu, Lei, Choi, Seung-Hoan, Sigurdsson, Sigurdur, Verhaaren, Benjamin F J, DeStefano, Anita L, Lambert, Jean-Charles, Cantor, Rita M, Struchalin, Maksim, Stankovich, Jim, Ibrahim-Verbaas, Carla A, Fleischman, Debra, Zijdenbos, Alex, den Heijer, Tom, Mazoyer, Bernard, Coker, Laura H, Enzinger, Christian, Danoy, Patrick, Carless, Melanie A, Amin, Najaf, Arfanakis, Konstantinos, van Buchem, Mark A, de Bruijn, Renée F A G, Beiser, Alexa, Dufouil, Carole, Huang, Juebin, Cavalieri, Margherita, Thomson, Russell, Niessen, Wiro J, Corvin, Aiden, Chibnik, Lori B, Gislason, Gauti K, Hofman, Albert, Pikula, Aleksandra, Amouyel, Philippe, Freeman, Kevin B, Phan, Thanh G, Oostra, Ben A, Nalls, Michael A, Uitterlinden, Andre G, Czisch, Michael, Au, Rhoda, Elbaz, Alexis, Beare, Richard J, van Swieten, John C, Lopez, Oscar, Harris, Tamara B, Chouraki, Vincent, Breteler, Monique M B, De Jager, Philip L, Becker, James T, Curran, Joanne E, Knopman, David, Fazekas, Franz, Wolf, Philip A, van der Lugt, Aad, Longstreth, W. T., Brown, Mathew A, Bennett, David A, van Duijn, Cornelia M, Davies, Gail, Mosley, Thomas H, Schmidt, Reinhold, de Almeida, Marcio A A, Appel, Katja, Duggirala, Ravi, Dyer, Thomas D, Erk, Susanne, Fagerness, Jesen, Fox, Peter T, Freimer, Nelson B, Gill, Michael, Göring, Harald H H, Bartecek, Richard, Hagler, Donald J, Hoehn, David, Holsboer, Florian, Hoogman, Martine, Hosten, Norbert, Jahanshad, Neda, Johnson, Matthew P, Kent, Jack W, Kochunov, Peter, Bergmann, Ørjan, Lancaster, Jack L, Lawrie, Stephen M, Liewald, David C, Mandl, René, Mattheisen, Manuel, Meisenzahl, Eva, Melle, Ingrid, Moses, Eric K, Mühleisen, Thomas W, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, Queensland Institute of Medical Research, Radboud University Medical Center [Nijmegen], Yale University School of Medicine, Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Universität Greifswald - University of Greifswald, Universität Heidelberg [Heidelberg], University Medical Center [Utrecht], University of Oslo (UiO), University of Toronto, National University of Ireland [Galway] (NUI Galway), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], University of Bergen (UiB), Harvard University [Cambridge], VU University Amsterdam, University of Edinburgh, Structure et Réactivité des Systèmes Moléculaires Complexes (SRSMC), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], National Institutes of Health [Bethesda] (NIH), Department of Forensic and Neurodevelopmental Sciences, King‘s College London, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Georgia State University, University System of Georgia (USG), Department of Psychiatry and Human Behavior [Irvine], University of California [Irvine] (UCI), Leiden University Medical Center (LUMC), Dundee Technopole, CXR Biosciences Ltd, University of Groningen [Groningen], Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland (RCSI), Department of Genetics, Southwest Foundation for Biomedical Research, Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], Neurology Division, Beaumont Hospital, Dublin 9, Ireland, Beaumont Hospital, The University of Texas Health Science Center at Houston (UTHealth), Center for Neurobehavioral Genetics, Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, Department of Computer Science, Durham University, Laboratoire des symbioses tropicales et méditerranéennes (UMR LSTM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], University of California, Institute of Neurology [London], University College of London [London] (UCL), University of California [San Francisco] (UCSF), Department of Medicine, University of Washington [Seattle], Erasmus University Medical Center [Rotterdam] (Erasmus MC), Centre Émile Durkheim (CED), Sciences Po Bordeaux - Institut d'études politiques de Bordeaux (IEP Bordeaux)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Salermo, Università degli Studi di Salerno (UNISA), School of Psychology, University of Queensland, University of Queensland [Brisbane], Hartford Hospital, Lancaster University, Centre for Advanced Imaging, McConnell Brain Imaging Centre (MNI), McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Stanley Center for Psychiatric Research, Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Faculteit Medische Wetenschappen/UMCG, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Perceptual and Cognitive Neuroscience (PCN), Biological Psychology, Neuroscience Campus Amsterdam - Brain Imaging, EMGO+ - Mental Health, EPIGEN Consortium, IMAGENConsortium, Saguenay Youth Study Group, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium, Psychiatry, NCA - Brain Imaging, EMGO - Mental health, Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Virology, Epidemiology, Clinical Chemistry, Erasmus MC other, Radiology & Nuclear Medicine, University of California (UC)-University of California (UC), Yale School of Medicine [New Haven, Connecticut] (YSM), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Universität Heidelberg [Heidelberg] = Heidelberg University, Harvard University, Vrije Universiteit Amsterdam [Amsterdam] (VU), University of California [Irvine] (UC Irvine), Universiteit Leiden, University of California (UC), University of California [San Francisco] (UC San Francisco), Università degli Studi di Salerno = University of Salerno (UNISA), University of Iceland [Reykjavik], McGill University, University of Bergen (UIB), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Bijvoet Center of Biomolecular Research, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, UMR5116, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), and McGill University-McGill University
Subjects: Netherlands Twin Register (NTR), Pathology, 110 012 Social cognition of verbal communication, [SDV]Life Sciences [q-bio], Hippocampus, Genome-wide association study, DCN PAC - Perception action and control, Hippocampal formation, physiopathology [Brain], Bioinformatics, 0302 clinical medicine, 130 000 Cognitive Neurology & Memory, TEMPORAL-LOBE EPILEPSY, 110 014 Public activities, Renal disorder [IGMD 9], 0303 health sciences, medicine.diagnostic_test, Translational research Immune Regulation [ONCOL 3], Brain, Human brain, Genomic disorders and inherited multi-system disorders [DCN PAC - Perception action and control IGMD 3], ALZHEIMERS-DISEASE, medicine.anatomical_structure, Brain size, genetics [Chromosomes, Human, Pair 12], genetics [Polymorphism, Single Nucleotide], Biomarker (medicine), NA+/H+ EXCHANGER, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Genetic Markers, medicine.medical_specialty, 110 000 Neurocognition of Language, DCN MP - Plasticity and memory, A neurocomputational model for the Processing of Linguistic Utterances based on the Unification-Space architecture [110 007 PLUS], BRAIN VOLUME, UNIFIED APPROACH, 110 013 Binding and the MUC-model, Neuroimaging, Biology, GENOTYPE IMPUTATION, Polymorphism, Single Nucleotide, Article, Genomic disorders and inherited multi-system disorders DCN MP - Plasticity and memory [IGMD 3], 03 medical and health sciences, AUTOMATED SEGMENTATION, Meta-Analysis as Topic, SDG 3 - Good Health and Well-being, ddc:570, FUNCTIONAL IMPLICATIONS, Genetics, medicine, Humans, GENOME-WIDE ASSOCIATION, 030304 developmental biology, Chromosomes, Human, Pair 12, Magnetic resonance imaging, Genetic Loci, physiopathology [Hippocampus], 110 009 The human brain and Chinese prosody, Genetics and epigenetic pathways of disease Genomic disorders and inherited multi-system disorders [NCMLS 6], HUMAN HEIGHT, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Contains fulltext : 108202.pdf (Publisher’s version ) (Closed access) Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 x 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 x 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 x 10(-7)). 01 mei 2012
Published: 2012

8. Glucose metabolism and smaller hippocampal volume in elderly people with normal cognitive function.

Author: Shima A, Noguchi-Shinohara M, Shibata S, Usui Y, Tatewaki Y, Thyreau B, Hata J, Ohara T, Honda T, Taki Y, Nakaji S, Maeda T, Mimura M, Nakashima K, Iga JI, Takebayashi M, Nishijo H, Ninomiya T, and Ono K
Abstract: We investigated associations of glycemic measures, and insulin resistance and secretion measures with hippocampal and subfield volumes. In this cross-sectional study, 7400 community-dwelling participants underwent brain MRI and health checkups between 2016 and 2018. Hemoglobin A 1c (HbA 1c ), glycated albumin (GA), homeostasis model assessment for insulin resistance (HOMA-IR), and HOMA of percent β-cell function (HOMA-β) were evaluated. The associations of each measure with a smaller volume of the hippocampus and twelve hippocampal subfields were investigated. As a result, higher HbA 1c or GA and lower HOMA-β levels were significantly associated with smaller volumes in multiple hippocampal subfields. Furthermore, even when we analyzed non-diabetic individuals, substantial associations remained between higher GA or lower HOMA-β levels and smaller volumes of the whole hippocampus or the fimbria. Our findings indicate that postprandial glucose fluctuations, postprandial hyperglycemia, and low insulin secretion have a specific effect on the development of smaller hippocampal volume, suggesting that primary prevention of diabetes and/or sufficient glucose control are important for the prevention of dementia., (© 2024. The Author(s).)
Published: 2024
Full Text: View/download PDF

9. Association between Gray and White Matter Lesions and Its Involvement in Clinical Symptoms of Alzheimer's-Type Dementia.

Author: Nakase T, Thyreau B, Tatewaki Y, Tomita N, Takano Y, Muranaka M, and Taki Y
Abstract: Background: Not only gray matter lesions (GMLs) but also white matter lesions (WMLs) can play important roles in the pathology of Alzheimer's disease (AD). The progression of cognitive impairment (CI) and behavioral and psychological symptoms of dementia (BPSD) might be caused by a concerted effect of both GML and WML., Objective: This study aimed to investigate the association between GML and WML and how they are involved in the symptoms of CI and BPSD in dementia patients by means of imaging technology., Methods: Patients in our memory clinic, who were diagnosed with AD-type dementia or amnestic mild cognitive impairment (aMCI) and had undergone both single-photon emission computed tomography (SPECT) and brain MRI, were consecutively enrolled ( n = 156; 61 males and 95 females; 79.8 ± 7.4 years old). Symptoms of CI and BPSD were obtained from patients' medical records. For the analysis of GMLs and WMLs, SPECT data and MRI T1-weighted images were used, respectively. This study followed the Declaration of Helsinki, and all procedures were approved by the institutional ethics committee., Results: According to a multivariate analysis, disorientation and disturbed attention demonstrated a relationship between the precuneus and WMLs in both hemispheres. Hyperactivity in BPSD showed multiple correlations between GMLs on both sides of the frontal cortex and WMLs. Patients with aMCI presented more multiple correlations between GMLs and WMLs compared with those with AD-type dementia regarding dementia symptoms including BPSD., Conclusion: The interaction between GMLs and WMLs may vary depending on the symptoms of CI and BPSD. Hyperactivity in BPSD may be affected by the functional relationship between GMLs and WMLs in the left and right hemispheres. The correlation between GMLs and WMLs may be changing in AD-type dementia and aMCI.
Published: 2023
Full Text: View/download PDF

10. Impact of hs-CRP concentration on brain structure alterations and cognitive trajectory in Alzheimer's disease.

Author: Zhang Y, Tatewaki Y, Nakase T, Liu Y, Tomita N, Thyreau B, Zheng H, Muranaka M, Takano Y, Nagasaka T, and Taki Y
Abstract: Introduction: Present study was to investigate hs-CRP concentration, brain structural alterations, and cognitive function in the context of AD [Subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD]., Methods: We retrospectively included 313 patients (Mean age = 76.40 years, 59 SCD, 101 MCI, 153 AD) in a cross-sectional analysis and 91 patients (Mean age = 75.83 years, 12 SCD, 43 MCI, 36 AD) in a longitudinal analysis. Multivariable linear regression was conducted to investigate the relationship between hs-CRP concentration and brain structural alterations, and cognitive function, respectively., Results: Hs-CRP was positively associated with gray matter volume in the left fusiform (β = 0.16, p FDR = 0.023) and the left parahippocampal gyrus (β = 0.16, p FDR = 0.029). Post hoc analysis revealed that these associations were mainly driven by patients with MCI and AD. The interaction of diagnosis and CRP was significantly associated with annual cognitive changes (β = 0.43, p = 0.008). Among these patients with AD, lower baseline CRP was correlated with greater future cognitive decline ( r = -0.41, p = 0.013)., Conclusion: Our study suggests that increased hs-CRP level may exert protective effect on brain structure alterations and future cognitive changes among patients already with cognitive impairment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Tatewaki, Nakase, Liu, Tomita, Thyreau, Zheng, Muranaka, Takano, Nagasaka and Taki.)
Published: 2023
Full Text: View/download PDF

11. Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study: Rationale, Design, and Background.

Author: Taira M, Mugikura S, Mori N, Hozawa A, Saito T, Nakamura T, Kiyomoto H, Kobayashi T, Ogishima S, Nagami F, Uruno A, Shimizu R, Kobayashi T, Yasuda J, Kure S, Sakurai M, Motoike IN, Kumada K, Nakaya N, Obara T, Oba K, Sekiguchi A, Thyreau B, Mutoh T, Takano Y, Abe M, Maikusa N, Tatewaki Y, Taki Y, Yaegashi N, Tomita H, Kinoshita K, Kuriyama S, Fuse N, and Yamamoto M
Abstract: The Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study (TMM Brain MRI Study) was established to collect multimodal information through neuroimaging and neuropsychological assessments to evaluate the cognitive function and mental health of residents who experienced the Great East Japan Earthquake (GEJE) and associated tsunami. The study also aimed to promote advances in personalized healthcare and medicine related to mental health and cognitive function among the general population. We recruited participants for the first (baseline) survey starting in July 2014, enrolling individuals who were participating in either the TMM Community-Based Cohort Study (TMM CommCohort Study) or the TMM Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). We collected multiple magnetic resonance imaging (MRI) sequences, including 3D T1-weighted sequences, magnetic resonance angiography (MRA), diffusion tensor imaging (DTI), pseudo-continuous arterial spin labeling (pCASL), and three-dimensional fluid-attenuated inversion recovery (FLAIR) sequences. To assess neuropsychological status, we used both questionnaire- and interview-based rating scales. The former assessments included the Tri-axial Coping Scale, Impact of Event Scale in Japanese, Profile of Mood States, and 15-item Depression, Anxiety, and Stress Scale, whereas the latter assessments included the Mini-Mental State Examination, Japanese version. A total of 12,164 individuals were recruited for the first (baseline) survey, including those unable to complete all assessments. In parallel, we returned the MRI results to the participants and subsequently shared the MRI data through the TMM Biobank. At present, the second (first follow-up) survey of the study started in October 2019 is underway. In this study, we established a large and comprehensive database that included robust neuroimaging data as well as psychological and cognitive assessment data. In combination with genomic and omics data already contained in the TMM Biobank database, these data could provide new insights into the relationships of pathological processes with neuropsychological disorders, including age-related cognitive impairment., Competing Interests: None, (Copyright © Japan Medical Association.)
Published: 2023
Full Text: View/download PDF

12. Impact of atrial fibrillation on the cognitive decline in Alzheimer's disease.

Author: Nakase T, Tatewaki Y, Thyreau B, Odagiri H, Tomita N, Yamamoto S, Takano Y, Muranaka M, and Taki Y
Subjects: Humans, Aged, Aged, 80 and over, Brain pathology, Retrospective Studies, Magnetic Resonance Imaging methods, Alzheimer Disease complications, Alzheimer Disease diagnostic imaging, Alzheimer Disease pathology, Atrial Fibrillation complications, Atrial Fibrillation diagnostic imaging, Atrial Fibrillation pathology, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction pathology
Abstract: Background: Atrial fibrillation (AF) is a strong risk factor for Alzheimer's disease (AD) independent of ischemic stroke. However, the clinicopathological impact of AF on the severity of AD has not been well elucidated. We aimed to investigate the clinical differences between dementia patients with AF and those without AF by means of imaging data., Methods: Following approval from the institutional ethics committee, patients with newly diagnosed AD or amnestic mild cognitive impairment (aMCI) were retrospectively screened (n = 170, 79.5 ± 7.4 years old). Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Based on the MRI data, the cerebral volume, cerebral microbleeds (CMBs), periventricular white matter lesions (WMLs), and deep WMLs were evaluated. The regional cerebral blood flow (rCBF) was measured using 123 I-IMP SPECT., Results: Of the patients, 14 (8.2%) and 156 (91.8%) had AF (AF group) and sinus rhythm (SR group), respectively. The AF group had significantly lower MMSE scores than the SR group (average [standard deviation (SD)]: 19.4 [4.4] and 22.0 [4.4], respectively; p = 0.0347). Cerebral volume and CMBs did not differ between the two groups. The periventricular WMLs, but not the deep WMLs, were significantly larger in the AF group than in the SR group (mean [SD] mL: 6.85 [3.78] and 4.37 [3.21], respectively; p = 0.0070). However, there was no significant difference in rCBF in the areas related to AD pathology between the two groups., Conclusion: AD and aMCI patients with AF showed worse cognitive decline along with larger periventricular WMLs compared to those with SR, although the reduction of rCBF was not different between patients with AF and SR. The white matter lesions may be a more important pathology than the impairment of cerebral blood flow in dementia patients with AF. A larger study is needed to confirm our findings in the future., (© 2023. The Author(s).)
Published: 2023
Full Text: View/download PDF

13. Impact of constipation on progression of Alzheimer's disease: A retrospective study.

Author: Nakase T, Tatewaki Y, Thyreau B, Mutoh T, Tomita N, Yamamoto S, Takano Y, Muranaka M, and Taki Y
Subjects: Humans, Retrospective Studies, Neuropsychological Tests, Magnetic Resonance Imaging, Constipation, Disease Progression, Alzheimer Disease pathology, Cognitive Dysfunction pathology
Abstract: Background and Purpose: In terms of the gut-brain axis, constipation has been considered to be an important factor of neurodegenerative diseases, although the exact mechanism is still controversial. Herein, we aimed to investigate the contribution of constipation to the progression of dementia in a retrospective study., Methods: Patients of Alzheimer's disease(AD) and amnestic mild cognitive impairment were consecutively screened between January 2015 and December 2020, and those of whom brain MRI and neuropsychological tests were performed twice were enrolled in this study. Participants were classified into with constipation (Cons[+], n = 20) and without constipation (Cons[-], n = 64) groups. Laboratory data at the first visit were used. Regression analysis was performed in MMSE, ADAS-Cog, and the volumes of hippocampus on MRI-MPRAGE images and deep white matter lesions (DWMLs) on MRI-FLAIR images obtained at two different time points., Results: The main finding was that the Cons[+] group showed 2.7 times faster decline in cognitive impairment compared with the Cons[-] group, that is, the liner coefficients of ADAS-Cog were 2.3544 points/year in the Cons[+] and 0.8592 points/year in the Cons[-] groups. Ancillary, changes of DWMLs showed significant correlation with the time span (p < 0.01), and the liner coefficients of DWMLs were 24.48 ml/year in the Cons[+] and 14.83 ml/year in the Cons[-] group, although annual rate of hippocampal atrophy was not different between the two groups. Moreover, serum homocysteine level at baseline was significantly higher in the Cons[+] group than Cons[-] group (14.6 ± 6.4 and 11.5 ± 4.2 nmol/ml, respectively: p = 0.03)., Conclusion: There is a significant correlation between constipation and faster progression of AD symptoms along with expansion of DWMLs., (© 2022 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)
Published: 2022
Full Text: View/download PDF

14. Higher-resolution quantification of white matter hypointensities by large-scale transfer learning from 2D images on the JPSC-AD cohort.

Author: Thyreau B, Tatewaki Y, Chen L, Takano Y, Hirabayashi N, Furuta Y, Hata J, Nakaji S, Maeda T, Noguchi-Shinohara M, Mimura M, Nakashima K, Mori T, Takebayashi M, Ninomiya T, and Taki Y
Subjects: Aged, Brain diagnostic imaging, Brain pathology, Humans, Japan, Machine Learning, Magnetic Resonance Imaging methods, Prospective Studies, White Matter diagnostic imaging
Abstract: White matter lesions (WML) commonly occur in older brains and are quantifiable on MRI, often used as a biomarker in Aging research. Although algorithms are regularly proposed that identify these lesions from T2-fluid-attenuated inversion recovery (FLAIR) sequences, none so far can estimate lesions directly from T1-weighted images with acceptable accuracy. Since 3D T1 is a polyvalent and higher-resolution sequence, it could be beneficial to obtain the distribution of WML directly from it. However a serious difficulty, both for algorithms and human, can be found in the ambiguities of brain signal intensity in T1 images. This manuscript shows that a cross-domain ConvNet (Convolutional Neural Network) approach can help solve this problem. Still, this is non-trivial, as it would appear to require a large and varied dataset (for robustness) labelled at the same high resolution (for spatial accuracy). Instead, our model was taught from two-dimensional FLAIR images with a loss function designed to handle the super-resolution need. And crucially, we leveraged a very large training set for this task, the recently assembled, multi-sites Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) cohort. We describe the two-step procedure that we followed to handle such a large number of imperfectly labeled samples. A large-scale accuracy evaluation conducted against FreeSurfer 7, and a further visual expert rating revealed that WML segmentation from our ConvNet was consistently better. Finally, we made a directly usable software program based on that trained ConvNet model, available at https://github.com/bthyreau/deep-T1-WMH., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
Full Text: View/download PDF

15. Association of the prefrailty with global brain atrophy and white matter lesions among cognitively unimpaired older adults: the Nakajima study.

Author: Noguchi-Shinohara M, Ono K, Yuki-Nozaki S, Iwasa K, Yokogawa M, Komai K, Thyreau B, Tatewaki Y, Taki Y, Shibata M, Ohara T, Hata J, Ninomiya T, and Yamada M
Subjects: Aged, Atrophy, Brain diagnostic imaging, Frail Elderly, Geriatric Assessment methods, Humans, Frailty, White Matter diagnostic imaging
Abstract: Physical frailty has been associated with adverse outcomes such as dementia. However, the underlying structural brain abnormalities of physical frailty are unclear. We investigated the relationship between physical frailty and structural brain abnormalities in 670 cognitively unimpaired individuals (mean age 70.1 years). Total brain volume (TBV), hippocampal volume (HV), total white matter hypointensities volume (WMHV), and estimated total intracranial volume (eTIV) on the 3D T1-weighted images were automatically computed using FreeSurfer software. Participants were divided into two states of physical frailty (robust vs. prefrail) based on the revised Japanese version of the Cardiovascular Health Study criteria. The multivariable-adjusted mean values of the TBV-to-eTIV ratio was significantly decreased, whereas that of the WMHV-to-eTIV ratio was significantly increased in the prefrail group compared with the robust group. Slowness, one of the components of physical frailty, was significantly associated with reduced TBV-to-eTIV and HV-to-eTIV ratios, and slowness and weakness were significantly associated with an increased WMHV-to-eTIV ratio. Our results suggest that the prefrail state is significantly associated with global brain atrophy and white matter hypointensities. Furthermore, slowness was significantly associated with hippocampal atrophy., (© 2022. The Author(s).)
Published: 2022
Full Text: View/download PDF

16. Impact of Catheter Ablation on Brain Microstructure and Blood Flow Alterations for Cognitive Improvements in Patients with Atrial Fibrillation: A Pilot Longitudinal Study.

Author: Tatewaki Y, Mutoh T, Sato H, Kobayashi A, Totsune T, Thyreau B, Sekiguchi A, Nakase T, Yagi T, and Taki Y
Abstract: Atrial fibrillation (AF) predisposes patients to develop cognitive decline and dementia. Clinical and epidemiological data propose that catheter ablation may provide further benefit to improve neurocognitive function in patients with AF, but the underlying mechanism is poorly available. Here, we conducted a pilot prospective study to investigate whether AF ablation can alter regional cerebral blood flow (rCBF) and brain microstructures, using multimodal magnetic resonance imaging (MRI) technique. Eight patients (63 ± 7 years) with persistent AF underwent arterial-spin labeling (ASL) perfusion, 3D T1-structural images and cognitive test batteries before and 6 months after intervention. ASL and structural MR images were spatially normalized, and the rCBF and cortical thickness of different brain areas were compared between pre- and 6-month post-treatment. Cognitive-psychological function was improved, and rCBF was significantly increased in the left posterior cingulate cortex (PCC) ( p = 0.013), whereas decreased cortical thickness was found in the left posterior insular cortex ( p = 0.023). Given that the PCC is a strategic site in the limbic system, while the insular cortex is known to play an important part in the central autonomic nervous system, our findings extend the hypothesis that autonomic system alterations are an important mechanism explaining the positive effect of AF ablation on cognitive function.
Published: 2022
Full Text: View/download PDF

17. Impact of medium-chain triglycerides on gait performance and brain metabolic network in healthy older adults: a double-blind, randomized controlled study.

Author: Mutoh T, Kunitoki K, Tatewaki Y, Yamamoto S, Thyreau B, Matsudaira I, Kawashima R, and Taki Y
Subjects: Aged, Female, Glucose, Humans, Male, Metabolic Networks and Pathways, Triglycerides, Brain, Gait
Abstract: Nutritional supplementation with medium-chain triglycerides (MCTs) has the potential to increase memory function in elderly patients with frailty and dementia. Our aim was to investigate the effects of MCT on cognitive and gait functions and their relationships with focal brain metabolism and functional connectivity even in healthy older adults. Participants were blindly randomized and allocated to two groups: 18 g/day of MCT oil and matching placebo formula (control) administered as a jelly stick (6 g/pack, ingested three times a day). Gait analysis during the 6-m walk test, cognition, brain focal glucose metabolism quantified by 18 F-fluorodeocyglucose positron emission tomography, and magnetic resonance imaging-based functional connectivity were assessed before and after a 3-month intervention. Sixty-three healthy, normal adults (females and males) were included. Compared with the control group, the MCT group showed better balance ability, as represented by the lower Lissajous index (23.1 ± 14.4 vs. 31.3 ± 18.9; P < 0.01), although no time × group interaction was observed in cognitive and other gait parameters. Moreover, MCT led to suppressed glucose metabolism in the right sensorimotor cortex compared with the control (P < 0.001), which was related to improved balance (r = 0.37; P = 0.04) along with increased functional connectivity from the ipsilateral cerebellar hemisphere. In conclusion, a 3-month MCT supplementation improves walking balance by suppressing glucose metabolism, which suggests the involvement of the cerebro-cerebellar network. This may reflect, at least in part, the inverse reaction of the ketogenic switch as a beneficial effect of long-term MCT dietary treatment., (© 2022. The Author(s), under exclusive licence to American Aging Association.)
Published: 2022
Full Text: View/download PDF

18. Voxel-Based Morphometry Reveals a Correlation Between Bone Mineral Density Loss and Reduced Cortical Gray Matter Volume in Alzheimer's Disease.

Author: Takano Y, Tatewaki Y, Mutoh T, Morota N, Matsudaira I, Thyreau B, Nagasaka T, Odagiri H, Yamamoto S, Arai H, and Taki Y
Abstract: Background : Decreased bone mineral density (BMD) was associated with poorer cognitive function and increased risk of Alzheimer's disease (AD). However, objective evidence for the relationship between osteoporosis and AD in humans has not been extensively described. Objectives : We aimed to evaluate the relationships between BMD and the cortical volumes of brain regions vulnerable to AD; hippocampus, parahippocampal gyrus, precuneus, posterior cingulate, and angular gyrus, using voxel-based morphometry (VBM), to investigate the association between bone loss and AD. Methods : A cohort of 149 consecutive elderly participants who complained of memory disturbance underwent high-resolution structural brain magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA). We used SPM12 software to conduct a voxel-based multiple regression analysis to examine the association between femoral neck BMD values and regional gray matter volume (rGMV) on structural T1-weighted MRI. Results : After adjusting for subject age, gender, total brain volume (TBV), and mini-mental state examination (MMSE) scores, the multiple regression analysis showed significant correlations between BMD loss and rGMV decline in the left precuneus, which is an important neural network hub vulnerable to AD. Conclusion : These data suggest that the bone and brain communicate with each other, as in "bone-brain crosstalk," and that control of BMD factors could contribute to cognitive function and help prevent AD., (Copyright © 2020 Takano, Tatewaki, Mutoh, Morota, Matsudaira, Thyreau, Nagasaka, Odagiri, Yamamoto, Arai and Taki.)
Published: 2020
Full Text: View/download PDF

19. Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images.

Author: Tatewaki Y, Mutoh T, Omodaka K, Thyreau B, Matsudaira I, Furukawa H, Yamada K, Kunitoki K, Kawashima R, Nakazawa T, and Taki Y
Subjects: Adult, Aged, Glaucoma diagnosis, Humans, Middle Aged, Myopia diagnosis, Organ Size, Eye diagnostic imaging, Eye pathology, Glaucoma diagnostic imaging, Glaucoma pathology, Imaging, Three-Dimensional, Magnetic Resonance Imaging
Abstract: Elongated axial length of the eye increases the morbidity of glaucoma. Myopia also associates with elongated axial length, and such ellipsoid shape of the eyeball strongly contributes its pathogenesis. Morphological features of the eyeballs, which could be important factors for developing glaucoma, have not been well described. The aim of this study was to investigate the three-dimensional (3D) topographic features of glaucomatous eyeballs with/without myopia to evaluate the potential of those features for predicting glaucoma. Using a 3.0-tesla MRI, volume-isotropic turbo-spin-echo acquisition T2-weighted images were obtained from 55 patients with glaucoma and 22 controls to delineate the eyeballs. Eyeball volumes, axial lengths and transverse lengths were semi-automatically calculated and compared between four groups: normal, myopia, glaucoma, and glaucoma with myopia. Both glaucoma and myopia increased the eyeball volume compared to the normal eyes. An increased anisotropy ratio (axial/transversus length) was observed in myopic eyes compared to normal, whereas in the glaucomatous eyes, with or without myopia, no increase in anisotropy ratio was observed. Increasing volume of eyes can be caused by myopia and glaucoma. Myopic eyes were ellipsoid in shape, but there was less anisotropy and a near-spherical shape in glaucomatous eyes, even in glaucomatous myopic eyes.
Published: 2019
Full Text: View/download PDF

20. Phase Difference-Enhanced Magnetic Resonance (MR) Imaging (PADRE) Technique for the Detection of Age-Related Microstructural Changes in Optic Radiation: Comparison with Diffusion Tensor Imaging (DTI).

Author: Tatewaki Y, Mutoh T, Thyreau B, Omodaka K, Murata T, Sekiguchi A, Nakazawa T, and Taki Y
Subjects: Adult, Age Factors, Aged, Brain pathology, Diffusion Tensor Imaging methods, Female, Geniculate Bodies diagnostic imaging, Humans, Image Enhancement methods, Male, Middle Aged, Nerve Fibers physiology, White Matter pathology, Magnetic Resonance Imaging methods, Optic Nerve diagnostic imaging, Visual Cortex diagnostic imaging
Abstract: BACKGROUND The optic radiation (OR) is a white-matter bundle connecting the lateral geniculate body and the visual cortex. Phase difference-enhanced imaging (PADRE) is a new MRI technique that is able to achieve precise delineation of the OR. The aim of this study was to investigate the effect of age on the volume and signal intensity of the OR using PADRE, and to establish a volumetric reference of the OR from a healthy population, compared with diffusion tensor imaging (DTI). MATERIAL AND METHODS Thirty-nine healthy volunteers underwent MR imaging with PADRE and DTI sequences on a 3.0-T scanner. For the volumetric analysis with PADRE, the OR corresponding to the external sagittal stratum was manually traced, while an automated thresholding method was used for the DTI-based volumetric analysis of the OR. RESULTS The mean right and left OR volumes measured from the PADRE images were 1469.0±242.4 mm³ and 1372.6±310.2 mm³, respectively. Although OR volume showed no significant correlation with age, the normalized OR signal intensity showed a linear correlation with increasing age (r²=0.50-0.53; P<0.01). The OR signal intensity on PADRE and DTI-related quantitative parameters for the OR showed significant correlations (r²=0.46-0.49; P<0.01). CONCLUSIONS The PADRE technique revealed exceptional preservation of OR volume, even in later life. Moreover, PADRE was able to detect age-related changes in signal intensity of the OR and may contribute to future analyses of pathological neurodegeneration in patients with glaucoma and multiple sclerosis.
Published: 2017
Full Text: View/download PDF

21. The neural basis of the imitation drive.

Author: Hanawa S, Sugiura M, Nozawa T, Kotozaki Y, Yomogida Y, Ihara M, Akimoto Y, Thyreau B, Izumi S, and Kawashima R
Subjects: Adolescent, Brain Mapping methods, Female, Humans, Male, Mirror Neurons physiology, Neural Pathways physiology, Young Adult, Drive, Gyrus Cinguli physiology, Imitative Behavior physiology, Magnetic Resonance Imaging, Motor Cortex physiology, Psychomotor Performance physiology
Abstract: Spontaneous imitation is assumed to underlie the acquisition of important skills by infants, including language and social interaction. In this study, functional magnetic resonance imaging (fMRI) was used to examine the neural basis of 'spontaneously' driven imitation, which has not yet been fully investigated. Healthy participants were presented with movie clips of meaningless bimanual actions and instructed to observe and imitate them during an fMRI scan. The participants were subsequently shown the movie clips again and asked to evaluate the strength of their 'urge to imitate' (Urge) for each action. We searched for cortical areas where the degree of activation positively correlated with Urge scores; significant positive correlations were observed in the right supplementary motor area (SMA) and bilateral midcingulate cortex (MCC) under the imitation condition. These areas were not explained by explicit reasons for imitation or the kinematic characteristics of the actions. Previous studies performed in monkeys and humans have implicated the SMA and MCC/caudal cingulate zone in voluntary actions. This study also confirmed the functional connectivity between Urge and imitation performance using a psychophysiological interaction analysis. Thus, our findings reveal the critical neural components that underlie spontaneous imitation and provide possible reasons why infants imitate spontaneously., (© The Author (2015). Published by Oxford University Press.)
Published: 2016
Full Text: View/download PDF

22. Developmental changes in brain activation involved in the production of novel speech sounds in children.

Author: Hashizume H, Taki Y, Sassa Y, Thyreau B, Asano M, Asano K, Takeuchi H, Nouchi R, Kotozaki Y, Jeong H, Sugiura M, and Kawashima R
Subjects: Adolescent, Brain Mapping, Cerebrovascular Circulation physiology, Child, Discrimination, Psychological physiology, Female, Humans, Japan, Language Tests, Magnetic Resonance Imaging, Male, Brain growth & development, Brain physiology, Language Development, Phonetics, Speech physiology
Abstract: Older children are more successful at producing unfamiliar, non-native speech sounds than younger children during the initial stages of learning. To reveal the neuronal underpinning of the age-related increase in the accuracy of non-native speech production, we examined the developmental changes in activation involved in the production of novel speech sounds using functional magnetic resonance imaging. Healthy right-handed children (aged 6-18 years) were scanned while performing an overt repetition task and a perceptual task involving aurally presented non-native and native syllables. Productions of non-native speech sounds were recorded and evaluated by native speakers. The mouth regions in the bilateral primary sensorimotor areas were activated more significantly during the repetition task relative to the perceptual task. The hemodynamic response in the left inferior frontal gyrus pars opercularis (IFG pOp) specific to non-native speech sound production (defined by prior hypothesis) increased with age. Additionally, the accuracy of non-native speech sound production increased with age. These results provide the first evidence of developmental changes in the neural processes underlying the production of novel speech sounds. Our data further suggest that the recruitment of the left IFG pOp during the production of novel speech sounds was possibly enhanced due to the maturation of the neuronal circuits needed for speech motor planning. This, in turn, would lead to improvement in the ability to immediately imitate non-native speech., (Copyright © 2014 Wiley Periodicals, Inc.)
Published: 2014
Full Text: View/download PDF

23. Spinal fMRI of interoceptive attention/awareness in experts and novices.

Author: Kashkouli Nejad K, Sugiura M, Thyreau B, Nozawa T, Kotozaki Y, Furusawa Y, Nishino K, Nukiwa T, and Kawashima R
Subjects: Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Rest physiology, Attention physiology, Awareness physiology, Mindfulness education, Spinal Cord physiology
Abstract: Many disciplines/traditions that promote interoceptive (inner sensation of body parts) attention/awareness (IAA) train practitioners to both attend to and be aware of interoceptive sensory experiences in body parts. The effect of such practices has been investigated in previous imaging studies but limited to cerebral neural activity. Here, for the first time, we studied the impact of these practices on the spinal neural activity of experts and novices. We also attempted to clarify the effect of constant and deep breathing, a paradigm utilized in concentration practices to avoid mind wandering, on IAA-related spinal neural activity. Subjects performed IAA tasks with and without a deep and constant breathing pattern in two sessions. Results showed that neural activity in the spinal segment innervating the attended-to body area increased in experts (P = 0.04) when they performed IAA and that this increase was significantly larger for experts versus novices in each of the sessions (P = 0.024). The significant effects of IAA and expertise on spinal neural activity are consistent with and elaborate on previous reports showing similar effects on cerebral neural activity. As the spinal cord directly innervates body parts, the results might indicate that IAA has an instantaneous (possibly beneficial) effect on the physical body after extended training.
Published: 2014
Full Text: View/download PDF

24. Correlations between brain structures and study time at home in healthy children: a longitudinal analysis.

Author: Asano M, Taki Y, Hashizume H, Takeuchi H, Thyreau B, Sassa Y, Asano K, and Kawashima R
Subjects: Adolescent, Brain growth & development, Child, Child, Preschool, Female, Gray Matter anatomy & histology, Gray Matter growth & development, Humans, Image Processing, Computer-Assisted, Intelligence Tests, Language Tests, Longitudinal Studies, Magnetic Resonance Imaging, Male, Organ Size, Regression Analysis, Sex Characteristics, Time Factors, White Matter anatomy & histology, White Matter growth & development, Brain anatomy & histology, Habits, Learning
Abstract: Introduction: Like sleeping and eating habits, the study habits adopted by children when they are at home are important contributors to lifestyle and they affect cognitive ability. It has recently been reported that sleeping and eating habits change the brain structure of children. However, no research on the effect of study habits at home on the brain structure of children has been conducted thus far. We investigated the effects of study habits at home on the brain structures of healthy children by examining correlations between study time at home and changes in brain structure over the course of 3 years., Methods: We used the brain magnetic resonance images of 229 healthy children aged 5.6-18.4 years and computed the changes (time 2-time 1) in regional gray matter and white matter volume (rWMV) using voxel-based morphometry. Whole-brain multiple regression analysis revealed a significant positive correlation between study time at home and changes in rWMV in the right superior frontal gyrus (SFG). Behaviorally, we found a significant positive correlation between study time at home and change in the verbal comprehension index (VCI), one of the subscales of the Wechsler Intelligence Scale for Children-third edition (WISC-III)., Results and Conclusions: Given that the SFG is involved in memory control and that the VCI measures abilities related to vocabulary, our results indicate that greater SFG involvement in the memorization component of longer study times may result in greater increases in the number of axons and more axon branching and myelination, causing plastic changes in the neural network involved in memory processes.
Published: 2014
Full Text: View/download PDF

25. A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults.

Author: Taki Y, Thyreau B, Kinomura S, Sato K, Goto R, Wu K, Kawashima R, and Fukuda H
Subjects: Adult, Aged, Female, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Personality Inventory, Regression Analysis, Sex Factors, Time Factors, Young Adult, Brain anatomy & histology, Brain physiology, Brain Mapping, Personality physiology
Abstract: To investigate whether personality traits affect the rate of decline of gray matter volume, we analyzed the relationships between personality traits and the annual rate of changes of gray matter volume in 274 healthy community dwelling subjects with a large age range by applying a longitudinal design over 6 years, using brain magnetic resonance images (MRI) and the Revised NEO Personality Inventory (NEO-PI-R) at baseline. Brain MRI data were processed using voxel-based morphometry with a custom template by applying the DARTEL diffeomorphic registration tool. For each subject, we used NEO-PI-R to evaluate the five major personality traits, including neuroticism, extraversion, openness, agreeableness, and conscientiousness. The results show that the annual rate of change in regional gray matter volume in the right inferior parietal lobule was correlated significantly and negatively with a personality of openness, which is known to be related to intellect, intellectual curiosity, and creativity adjusting for age, gender, and intracranial volume. This result indicates that subjects with a personality trait of less openness have an accelerated loss of gray matter volume in the right inferior parietal lobule, compared with subjects with a personality trait of more openness. Because the right inferior parietal lobule is involved in higher cognitive function such as working memory and creativity, a personality trait of openness is thought to be important for preserving gray matter volume and cognitive function of the right inferior parietal lobule in healthy adults., (Copyright © 2012 Wiley Periodicals, Inc.)
Published: 2013
Full Text: View/download PDF

26. Correlation between high-sensitivity C-reactive protein and brain gray matter volume in healthy elderly subjects.

Author: Taki Y, Thyreau B, Kinomura S, Sato K, Goto R, Wu K, Kakizaki M, Tsuji I, Kawashima R, and Fukuda H
Subjects: Aged, Asymptomatic Diseases, Blood Pressure, Cross-Sectional Studies, Disease Progression, Female, Humans, Inflammation, Intracranial Arteriosclerosis pathology, Japan, Lipids blood, Male, Organ Size, Reference Values, Temporal Lobe pathology, Brain anatomy & histology, C-Reactive Protein analysis, Magnetic Resonance Imaging, Neuroimaging
Abstract: Although elevated serum high-sensitivity C-reactive protein (hsCRP) is related to atherosclerosis, brain infarction, and cognitive decline, it has not been clarified whether increased hsCRP is associated with the decline in brain gray matter volume. Therefore, the purpose of this study was to determine the relationship between hsCRP levels and brain regional gray matter volume using brain magnetic resonance imaging (MRI) data from 109 community-dwelling healthy elderly subjects. Brain MRIs were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra (DARTEL) procedure. We found a significant negative correlation between regional gray matter volume of the posterior and lateral aspects of the left temporal cortex and hsCRP level after adjusting for age, gender, and intracranial volume. Our results suggest that subjects who have mild inflammation related to arteriosclerosis have decreased regional gray matter volume in the posterior and lateral aspects of the left temporal cortex. Thus, preventing the progression of arteriosclerosis may be important for preventing a decrease in gray matter volume in healthy elderly subjects., (Copyright © 2012 Wiley Periodicals, Inc.)
Published: 2013
Full Text: View/download PDF

27. A longitudinal study of age- and gender-related annual rate of volume changes in regional gray matter in healthy adults.

Author: Taki Y, Thyreau B, Kinomura S, Sato K, Goto R, Wu K, Kawashima R, and Fukuda H
Subjects: Adult, Aged, Aged, 80 and over, Female, Healthy Volunteers, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult, Aging pathology, Brain pathology
Abstract: The aim of this study was to analyze correlations among the annual rate of gray matter volume change, age, gender, and cerebrovascular risk factors in 381 healthy community-dwelling subjects with a large age range by applying a longitudinal design over 6 years using brain magnetic resonance images (MRIs). Brain MRI data were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra procedure. The annual rate of regional gray matter volume change showed significant positive correlations with age in several regions, including the bilateral temporal pole, caudate nucleus, ventral and dorsolateral prefrontal cortices, insula, hippocampus, and temporoparietal cortex, whereas significant negative correlations with age were observed in several regions including the bilateral cingulate gyri and anterior lobe of the cerebellum. Additionally, a significant age-by-gender interaction was found for the annual rate of regional gray matter volume change in the bilateral hippocampus. No significant correlations were observed between the annual rate of regional gray matter volume change and body mass index or systolic blood pressure. A significant positive correlation between the annual rate of gray matter volume change and age indicates that the region shows not linear but accelerated gray matter loss with age. Therefore, evaluating the annual rate of the gray matter volume change with age in healthy subjects is important in understanding how gray matter volume changes with aging in each brain region and in anticipating what cognitive functions are likely to show accelerated decline with aging., (Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.)
Published: 2013
Full Text: View/download PDF

28. Linear and curvilinear correlations of brain gray matter volume and density with age using voxel-based morphometry with the Akaike information criterion in 291 healthy children.

Author: Taki Y, Hashizume H, Thyreau B, Sassa Y, Takeuchi H, Wu K, Kotozaki Y, Nouchi R, Asano M, Asano K, Fukuda H, and Kawashima R
Subjects: Adolescent, Child, Child, Preschool, Cross-Sectional Studies, Female, Humans, Magnetic Resonance Imaging, Male, Aging, Brain growth & development, Image Interpretation, Computer-Assisted methods
Abstract: We examined linear and curvilinear correlations of gray matter volume and density in cortical and subcortical gray matter with age using magnetic resonance images (MRI) in a large number of healthy children. We applied voxel-based morphometry (VBM) and region-of-interest (ROI) analyses with the Akaike information criterion (AIC), which was used to determine the best-fit model by selecting which predictor terms should be included. We collected data on brain structural MRI in 291 healthy children aged 5-18 years. Structural MRI data were segmented and normalized using a custom template by applying the diffeomorphic anatomical registration using exponentiated lie algebra (DARTEL) procedure. Next, we analyzed the correlations of gray matter volume and density with age in VBM with AIC by estimating linear, quadratic, and cubic polynomial functions. Several regions such as the prefrontal cortex, the precentral gyrus, and cerebellum showed significant linear or curvilinear correlations between gray matter volume and age on an increasing trajectory, and between gray matter density and age on a decreasing trajectory in VBM and ROI analyses with AIC. Because the trajectory of gray matter volume and density with age suggests the progress of brain maturation, our results may contribute to clarifying brain maturation in healthy children from the viewpoint of brain structure., (Copyright © 2012 Wiley Periodicals, Inc.)
Published: 2013
Full Text: View/download PDF

29. Linear and curvilinear correlations of brain white matter volume, fractional anisotropy, and mean diffusivity with age using voxel-based and region-of-interest analyses in 246 healthy children.

Author: Taki Y, Thyreau B, Hashizume H, Sassa Y, Takeuchi H, Wu K, Kotozaki Y, Nouchi R, Asano M, Asano K, Fukuda H, and Kawashima R
Subjects: Adolescent, Anisotropy, Child, Child, Preschool, Diffusion Tensor Imaging, Female, Humans, Image Interpretation, Computer-Assisted, Male, Nerve Fibers, Myelinated, Brain growth & development
Abstract: In this study, we examined linear and curvilinear correlations of fractional anisotropy (FA), mean diffusivity (MD), and white matter volume with age by using brain structural and diffusion-tensor magnetic resonance imaging (MRI) in a large number of healthy children and voxel-based morphometry (VBM) and region-of-interest (ROI) analyses. We collected data by brain structural MRI in 246 healthy children, aged 5-18 years. FA and MD images were normalized using the normalization parameter of the corresponding structural MRI. Next, we analyzed the correlations between FA and age and between MD and age by estimating linear and logarithmic functions. We also analyzed the correlation between white matter volume and age by linear, quadratic, and cubic functions. Correlations between FA and age and between MD and age showed exponential trajectories in most ROIs in boys and girls, except for several fibers, such as the corpus callosum connecting the bilateral rectal gyri in boys. The correlation between white matter volume and age showed significant positive linear trajectories in most ROIs in boys and girls, except for a few fibers, such as the bilateral uncinate fasciculus. Additionally, maturational rates differed among major fibers, and in girls, the left superior longitudinal fasciculus, which connects the frontal and temporal lobes, showed a slower rate of maturation than other fibers. Our results may help to clarify the mechanisms of normal brain maturation from the viewpoint of brain white matter., (Copyright © 2012 Wiley Periodicals, Inc.)
Published: 2013
Full Text: View/download PDF

30. Neural correlates of deception in social contexts in normally developing children.

Author: Yokota S, Taki Y, Hashizume H, Sassa Y, Thyreau B, Tanaka M, and Kawashima R
Abstract: Deception is related to the ability to inhibit prepotent responses and to engage in mental tasks such as anticipating responses and inferring what another person knows, especially in social contexts. However, the neural correlates of deception processing, which requires mentalizing, remain unclear. Using functional magnetic resonance imaging (fMRI), we examined the neural correlates of deception, including mentalization, in social contexts in normally developing children. Healthy right-handed children (aged 8-9 years) were scanned while performing interactive games involving deception. The games varied along two dimensions: the type of reply (deception and truth) and the type of context (social and less social). Participants were instructed to deceive a witch and to tell the truth to a girl. Under the social-context conditions, participants were asked to consider what they inferred about protagonists' preferences from their facial expressions when responding to questions. Under the less-social-context conditions, participants did not need to consider others' preferences. We found a significantly greater response in the right precuneus under the social-context than under less-social-context conditions. Additionally, we found marginally greater activation in the right inferior parietal lobule (IPL) under the deception than under the truth condition. These results suggest that deception in a social context requires not only inhibition of prepotent responses but also engagement in mentalizing processes. This study provides the first evidence of the neural correlates of the mentalizing processes involved in deception in normally developing children.
Published: 2013
Full Text: View/download PDF

31. Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

Author: Wu K, Taki Y, Sato K, Hashizume H, Sassa Y, Takeuchi H, Thyreau B, He Y, Evans AC, Li X, Kawashima R, and Fukuda H
Subjects: Adolescent, Age Factors, Brain growth & development, Brain physiology, Brain Mapping, Child, Child, Preschool, Female, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Nerve Net growth & development, Nerve Net physiology, Neural Pathways growth & development, Neural Pathways physiology, Sex Factors, Brain anatomy & histology, Cognition physiology, Intelligence physiology, Nerve Net anatomy & histology, Neural Pathways anatomy & histology
Abstract: Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.
Published: 2013
Full Text: View/download PDF

32. Schizophrenia as a network disease: disruption of emergent brain function in patients with auditory hallucinations.

Author: Rish I, Cecchi G, Thyreau B, Thirion B, Plaze M, Paillere-Martinot ML, Martelli C, Martinot JL, and Poline JB
Subjects: Adult, Brain pathology, Female, Humans, Male, Middle Aged, Models, Neurological, Nerve Net pathology, Schizophrenia pathology, Statistics as Topic, Young Adult, Brain physiopathology, Hallucinations complications, Nerve Net physiopathology, Schizophrenia complications, Schizophrenia physiopathology
Abstract: Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, "emergent" working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests.
Published: 2013
Full Text: View/download PDF

33. PyXNAT: XNAT in Python.

Author: Schwartz Y, Barbot A, Thyreau B, Frouin V, Varoquaux G, Siram A, Marcus DS, and Poline JB
Abstract: As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, investigators rely more and more heavily on scripting using high-level languages to automate data management and processing tasks. For this, a structured and programmatic access to the data store is necessary. Web services are a first step toward this goal. They however lack in functionality and ease of use because they provide only low-level interfaces to databases. We introduce here PyXNAT, a Python module that interacts with The Extensible Neuroimaging Archive Toolkit (XNAT) through native Python calls across multiple operating systems. The choice of Python enables PyXNAT to expose the XNAT Web Services and unify their features with a higher level and more expressive language. PyXNAT provides XNAT users direct access to all the scientific packages in Python. Finally PyXNAT aims to be efficient and easy to use, both as a back-end library to build XNAT clients and as an alternative front-end from the command line.
Published: 2012
Full Text: View/download PDF

34. Correlations among brain gray matter volumes, age, gender, and hemisphere in healthy individuals.

Author: Taki Y, Thyreau B, Kinomura S, Sato K, Goto R, Kawashima R, and Fukuda H
Subjects: Adult, Aged, Cerebrospinal Fluid metabolism, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Young Adult, Aging physiology, Cerebrum anatomy & histology, Health, Sex Characteristics
Abstract: To determine the relationship between age and gray matter structure and how interactions between gender and hemisphere impact this relationship, we examined correlations between global or regional gray matter volume and age, including interactions of gender and hemisphere, using a general linear model with voxel-based and region-of-interest analyses. Brain magnetic resonance images were collected from 1460 healthy individuals aged 20-69 years; the images were linearly normalized and segmented and restored to native space for analysis of global gray matter volume. Linearly normalized images were then non-linearly normalized and smoothed for analysis of regional gray matter volume. Analysis of global gray matter volume revealed a significant negative correlation between gray matter ratio (gray matter volume divided by intracranial volume) and age in both genders, and a significant interaction effect of age × gender on the gray matter ratio. In analyzing regional gray matter volume, the gray matter volume of all regions showed significant main effects of age, and most regions, with the exception of several including the inferior parietal lobule, showed a significant age × gender interaction. Additionally, the inferior temporal gyrus showed a significant age × gender × hemisphere interaction. No regional volumes showed significant age × hemisphere interactions. Our study may contribute to clarifying the mechanism(s) of normal brain aging in each brain region.
Published: 2011
Full Text: View/download PDF

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources

Refine your results

34 results on '"Thyreau B"'

1. Brain charts for the human lifespan

2. Publisher Correction: Brain charts for the human lifespan

3. Brain charts for the human lifespan

4. Brain charts for the human lifespan

5. Brain charts for the human lifespan (vol 604, pg 525, 2022)

6. Brain charts for the human lifespan

7. Identification of common variants associated with human hippocampal and intracranial volumes

8. Glucose metabolism and smaller hippocampal volume in elderly people with normal cognitive function.

9. Association between Gray and White Matter Lesions and Its Involvement in Clinical Symptoms of Alzheimer's-Type Dementia.

10. Impact of hs-CRP concentration on brain structure alterations and cognitive trajectory in Alzheimer's disease.

11. Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study: Rationale, Design, and Background.

12. Impact of atrial fibrillation on the cognitive decline in Alzheimer's disease.

13. Impact of constipation on progression of Alzheimer's disease: A retrospective study.

14. Higher-resolution quantification of white matter hypointensities by large-scale transfer learning from 2D images on the JPSC-AD cohort.

15. Association of the prefrailty with global brain atrophy and white matter lesions among cognitively unimpaired older adults: the Nakajima study.

16. Impact of Catheter Ablation on Brain Microstructure and Blood Flow Alterations for Cognitive Improvements in Patients with Atrial Fibrillation: A Pilot Longitudinal Study.

17. Impact of medium-chain triglycerides on gait performance and brain metabolic network in healthy older adults: a double-blind, randomized controlled study.

18. Voxel-Based Morphometry Reveals a Correlation Between Bone Mineral Density Loss and Reduced Cortical Gray Matter Volume in Alzheimer's Disease.

19. Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images.

20. Phase Difference-Enhanced Magnetic Resonance (MR) Imaging (PADRE) Technique for the Detection of Age-Related Microstructural Changes in Optic Radiation: Comparison with Diffusion Tensor Imaging (DTI).

21. The neural basis of the imitation drive.

22. Developmental changes in brain activation involved in the production of novel speech sounds in children.

23. Spinal fMRI of interoceptive attention/awareness in experts and novices.

24. Correlations between brain structures and study time at home in healthy children: a longitudinal analysis.

25. A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults.

26. Correlation between high-sensitivity C-reactive protein and brain gray matter volume in healthy elderly subjects.

27. A longitudinal study of age- and gender-related annual rate of volume changes in regional gray matter in healthy adults.

28. Linear and curvilinear correlations of brain gray matter volume and density with age using voxel-based morphometry with the Akaike information criterion in 291 healthy children.

29. Linear and curvilinear correlations of brain white matter volume, fractional anisotropy, and mean diffusivity with age using voxel-based and region-of-interest analyses in 246 healthy children.

30. Neural correlates of deception in social contexts in normally developing children.

31. Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

32. Schizophrenia as a network disease: disruption of emergent brain function in patients with auditory hallucinations.

33. PyXNAT: XNAT in Python.

34. Correlations among brain gray matter volumes, age, gender, and hemisphere in healthy individuals.

Catalog

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Database

Publisher

34 results on '"Thyreau B"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources