Search

Your search keyword '"White, Simon [0000-0001-8642-7037]"' showing total 14 results
Start Over Author "White, Simon [0000-0001-8642-7037]" Search Limiters Available in Library Collection
14 results on '"White, Simon [0000-0001-8642-7037]"'

1. 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
Full Text
View/download PDF

2. Willingness of children and adolescents to have a COVID-19 vaccination: Results of a large whole schools survey in England

Author

Stephen Puntis, Simon R. White, Daniel Freeman, Jonathan Herring, Andrew J. Pollard, Karen L. Mansfield, Alice Townsend, Mina Fazel, Russell M Viner, White, Simon [0000-0001-8642-7037], Apollo - University of Cambridge Repository, and White, Simon R [0000-0001-8642-7037]

Subjects
Community cohesion, School, medicine.medical_specialty, Government, Public health, business.industry, COVID19, media_common.quotation_subject, education, Vaccination, General Medicine, Mental health, Social deprivation, Feeling, Family medicine, medicine, Child and adolescent, business, Socioeconomic status, Vaccine hesitancy, Research Paper, media_common
Abstract

Background: Vaccine hesitancy has affected COVID-19 adult vaccination programs in many countries. Data on hesitancy amongst child and adolescent populations is largely confined to parent opinion. We investigated the characteristics of vaccine hesitant children and adolescents using results from a large, school-based self-report survey of the willingness to have a COVID-19 vaccination in students aged 9 –18 years in England. Methods: Data from the OxWell Student Survey on mental health, life experiences and behaviours were used, collected from four counties across England. Local authority partners recruited schools. The vaccine hesitancy question gave six response options and were clustered to inform delivery: eager and willing were categorised as vaccination ‘opt-in’, don't know and not bothered categorised as ‘undecided’, and unwilling and anti-vaccination categorised as ‘opt-out’. We conducted a multinomial regression to determine associations between vaccine hesitancy and sociodemographic, health behaviour and social connection variables. Findings: 27,910 students from 180 schools answered the vaccine hesitancy question between 14th May and 21st July 2021, of whom 13984 (50.1%) would opt-in to take a vaccination, 10322 (37.0%) were undecided, and 3604 (12.9%) would opt-out. A lower percentage of younger students reported that they would opt-in to vaccination, for example, 35.7% of 9-year-olds and 51.3% of 13-year-olds compared to 77.8% of 17-year-olds would opt-in to take a vaccination. Students who were ‘opt-out’ or ‘undecided’ (a combined ‘vaccine hesitant’ group) were more likely to come from deprived socioeconomic contexts with higher rates of home rental versus home ownership and their school locations were more likely to be in areas of greater deprivation. They were more likely to smoke or vape, spend longer on social media, feel that they did not belong in their school community but had lower levels of anxiety and depression. The vaccine hesitant students- the undecided and opt-out groups- were similar in profile, although the opt-out students had higher reported confirmed or probable previous COVID-19 infection than the opt-in group, whereas those undecided, did not. Interpretation: If government vaccination strategies move towards vaccinating younger school-aged students, efforts to increase vaccination uptake may be necessary. Compared with students who would opt-in, those who were vaccine hesitant had greater indicators of social deprivation and felt a lack of community cohesion by not feeling a sense of belonging at their school. There were indications that those students who would opt-out had higher levels of marginalisation and mistrust. If programmes are rolled out, focus on hesitant younger students will be important, targeting more marginalised and deprived young people with information from trusted sources utilising social media; improving access to vaccination centres with provision both in and outside school; and addressing fears and worries about the effects of the vaccine. The main limitation of this study is that the participant group may not be wholly representative of England or the UK, which may bias population-level estimates of willingness to be vaccinated. Funding: The Westminster Foundation, the National Institute for Health Research (NIHR) Applied Research Collaboration Oxford and Thames Valley at Oxford Health NHS Foundation Trust and the NIHR Oxford Health Biomedical Research Centre.

Published
2021

3. Detection of quantitative trait loci from RNA-seq data with or without genotypes using BaseQTL

Author

Colin Starr, Simon R. White, Wei-Yu Lin, Paul D. W. Kirk, Chris Wallace, Elena Vigorito, Vigorito, Elena [0000-0001-6230-3849], Kirk, Paul [0000-0002-5931-7489], White, Simon [0000-0001-8642-7037], Wallace, Chris [0000-0001-9755-1703], and Apollo - University of Cambridge Repository

Subjects
Regulation of gene expression, 2 Aetiology, Computer Networks and Communications, Bayesian probability, Human Genome, 4202 Epidemiology, 42 Health Sciences, RNA-Seq, Computational biology, Quantitative trait locus, Article, 3105 Genetics, Computer Science Applications, FOS: Biological sciences, Expression quantitative trait loci, Genotype, Gene expression, Computer Science (miscellaneous), Genetics, 2.1 Biological and endogenous factors, Gene, 31 Biological Sciences
Abstract

Detecting genetic variants associated with traits (quantitative trait loci, QTL) requires genotyped study individuals. Here we describe BaseQTL, a Bayesian method that exploits allele-specific expression to map molecular QTL from sequencing reads (eQTL for gene expression) even when no genotypes are available. When used with genotypes to map eQTL, BaseQTL has lower error rates and increased power compared with existing QTL mapping methods. Running without genotypes limits how many tests can be performed, but due to the proximity of QTL variants to gene bodies, the 2.8% of variants within a 100 kB window that could be tested contained 26% of eQTL detectable with genotypes. eQTL effect estimates were invariably consistent between analyses performed with and without genotypes. Often, sequencing data may be generated in the absence of genotypes on patients and controls in differential expression studies, and we identified an apparent psoriasis-specific eQTL for GSTP1 in one such dataset, providing new insights into disease-dependent gene regulation. BaseQTL is a Bayesian method to map molecular QTL affecting allele-specific expression even when no genotypes are available. It is well suited to discover eQTLs hidden in a wealth of RNA-seq data to unravel molecular mechanisms underpinning disease.

Published
2021

4. A novel equivalence probability weighted power prior for using historical control data in an adaptive clinical trial design: a comparison to standard methods

Author

Nicky Best, Adrian Mander, Maxine Bennett, Simon R. White, Bennett, Maxine [0000-0001-6298-519X], White, Simon [0000-0001-8642-7037], Best, Nicky [0000-0003-4120-9727], and Apollo - University of Cambridge Repository

Subjects
Statistics and Probability, Computer science, Bayesian probability, 01 natural sciences, Bayesian, law.invention, borrowing, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Statistics, Prior probability, Main Paper, adaptive design, Humans, Pharmacology (medical), 030212 general & internal medicine, 0101 mathematics, Equivalence (measure theory), priors, Probability, Pharmacology, Adaptive clinical trial, Bayes Theorem, Interim analysis, historical data, Research Design, Sample Size, Binary data, Main Papers, Type I and type II errors
Abstract

Funder: National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre, A standard two-arm randomised controlled trial usually compares an intervention to a control treatment with equal numbers of patients randomised to each treatment arm and only data from within the current trial are used to assess the treatment effect. Historical data are used when designing new trials and have recently been considered for use in the analysis when the required number of patients under a standard trial design cannot be achieved. Incorporating historical control data could lead to more efficient trials, reducing the number of controls required in the current study when the historical and current control data agree. However, when the data are inconsistent, there is potential for biased treatment effect estimates, inflated type I error and reduced power. We introduce two novel approaches for binary data which discount historical data based on the agreement with the current trial controls, an equivalence approach and an approach based on tail area probabilities. An adaptive design is used where the allocation ratio is adapted at the interim analysis, randomising fewer patients to control when there is agreement. The historical data are down-weighted in the analysis using the power prior approach with a fixed power. We compare operating characteristics of the proposed design to historical data methods in the literature: the modified power prior; commensurate prior; and robust mixture prior. The equivalence probability weight approach is intuitive and the operating characteristics can be calculated exactly. Furthermore, the equivalence bounds can be chosen to control the maximum possible inflation in type I error.

Published
2021

5. Characterising group-level brain connectivity: A framework using Bayesian exponential random graph models

Author

Cam-CAN, Richard N. Henson, Linda Geerligs, Brieuc Lehmann, Simon R. White, Henson, Rik [0000-0002-0712-2639], White, Simon [0000-0001-8642-7037], and Apollo - University of Cambridge Repository

Subjects
Theoretical computer science, Group studies, Computer science, Cognitive Neuroscience, Models, Neurological, Bayesian probability, Individuality, Network neuroscience, Bayesian ERGM, 050105 experimental psychology, Task (project management), lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Fmri, Neural Pathways, Exponential random graph models, Humans, 0501 psychology and cognitive sciences, Categorical variable, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Structure (mathematical logic), Brain Mapping, Models, Statistical, Neuro- en revalidatiepsychologie, Group (mathematics), 05 social sciences, Neuropsychology and rehabilitation psychology, Brain, Bayes Theorem, Cognitive artificial intelligence, Magnetic Resonance Imaging, Range (mathematics), Neurology, Exponential Random Graph Model (ERGM), Nerve Net, 030217 neurology & neurosurgery
Abstract

Contains fulltext : 226126.pdf (Publisher’s version ) (Open Access) The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of an entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brain’s functional connectivity structure across a group of young individuals and a group of old individuals. 12 p.

Published
2021

6. Assessing dynamic functional connectivity in heterogeneous samples

Author

Simon R. White, Richard N. Henson, Brieuc Lehmann, Linda Geerligs, Cam-CAN, Lehmann, Brieuc [0000-0002-7302-4391], White, Simon [0000-0001-8642-7037], Henson, Rik [0000-0002-0712-2639], Apollo - University of Cambridge Repository, White, SR [0000-0001-8642-7037], and Henson, RN [0000-0002-0712-2639]

Subjects
Group studies, Computer science, Cognitive Neuroscience, Cam-CAN, Article, 030218 nuclear medicine & medical imaging, lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, Statistics, Connectome, Image Processing, Computer-Assisted, Humans, Computer Simulation, Spurious relationship, Resting state, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Dynamic functional connectivity, Hyperparameter, Modularity (networks), Resting state fMRI, business.industry, Action, intention, and motor control, Autocorrelation, Perception, Action and Control [DI-BCB_DCC_Theme 2], Pattern recognition, Magnetic Resonance Imaging, Level of measurement, Neurology, Data Interpretation, Statistical, FMRI, Neurovascular Coupling, Noise (video), Artificial intelligence, Older people, Psychology, business, 030217 neurology & neurosurgery
Abstract

Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brain's functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC., Graphical abstract fx1, Highlights • Estimates of dFC may be affected by various sources of between-people heterogeneity. • We simulated fMRI data to investigate the effect of such heterogeneity on dFC. • Differences in estimated dFC resulted from non-dynamic features of the data. • Choice of parameters in common methods produced spurious group differences in dFC.

Published
2017

7. Waves of Maturation and Senescence in Micro-structural MRI Markers of Human Cortical Myelination over the Lifespan

Author

Edward T. Bullmore, Donatas Sederevicius, Christian K. Tamnes, Kristine B. Walhovd, Anders M. Fjell, Atle Bjørnerud, Petra E. Vértes, Lars T. Westlye, Kirstie Whitaker, Aaron Alexander-Bloch, Rafael Romero Garcia, Simon R. White, František Váša, Håkon Grydeland, Ameera X. Patel, Vertes, Petra [0000-0002-0992-3210], Whitaker, Kirstie [0000-0001-8498-4059], White, Simon [0000-0001-8642-7037], Bullmore, Edward [0000-0002-8955-8283], and Apollo - University of Cambridge Repository

Subjects
Senescence, Adult, Male, Adolescent, Cognitive Neuroscience, Longevity, Sensory system, micro-structure, Biology, 050105 experimental psychology, Lateralization of brain function, 03 medical and health sciences, Cellular and Molecular Neuroscience, Myelin, Young Adult, 0302 clinical medicine, medicine, Connectome, Humans, cortical development, 0501 psychology and cognitive sciences, 10. No inequality, Child, Myelin Sheath, Aged, Aged, 80 and over, Cerebral Cortex, medicine.diagnostic_test, 05 social sciences, Magnetic resonance imaging, Original Articles, Human brain, Middle Aged, Magnetic Resonance Imaging, 3. Good health, myelin, medicine.anatomical_structure, Myelinogenesis, Female, Neuroscience, lifespan, 030217 neurology & neurosurgery
Abstract

Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker sensitive to myelin, we studied fine-grained age differences to deduce waves of growth, stability, and decline of cortical myelination over the life-cycle. In 484 participants, aged 8-85 years, we fitted smooth growth curves to T1- to T2-weighted ratio in each of 360 regions from one of 7 cytoarchitectonic classes. From the first derivatives of these generally inverted-U trajectories, we defined three milestones: the age at peak growth; the age at onset of a stable plateau; and the age at the onset of decline. Age at peak growth had a bimodal distribution comprising an early (pre-pubertal) wave of primary sensory and motor cortices and a later (post-pubertal) wave of association, insular and limbic cortices. Most regions reached stability in the 30s but there was a second wave reaching stability in the 50s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60s, but in other left hemisphere regions, there was no significant decline from the stable plateau. Network analysis of the micro-structural connectome revealed that late developing (second wave) regions had significantly higher degree and other measures of centrality. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination, which may be relevant to the onset of neuropsychiatric disorders, and dementia, and the staged acquisition and decline of motor and cognitive skills over the course of the life-cycle.

Published
2019

8. Sample size and classification error for Bayesian change-point models with unlabelled sub-groups and incomplete follow-up

Author

Graciela Muniz-Terrera, Fiona E. Matthews, Simon R. White, White, Simon [0000-0001-8642-7037], Matthews, Fiona [0000-0002-1728-2388], and Apollo - University of Cambridge Repository

Subjects
Statistics and Probability, Epidemiology, Computer science, Bayesian probability, Specific time, change-point regression, Neuropsychological Tests, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Health Information Management, Statistics, broken-stick, Econometrics, Change-point, Humans, Point (geometry), Cognitive Dysfunction, 0101 mathematics, Cognitive decline, Models, Statistical, Bayes Theorem, Articles, cognitive decline, simulation study, sample size, Markov Chains, classification, Sample size determination, Data Interpretation, Statistical, Trajectory, Mini-Mental State Examination, Monte Carlo Method, 030217 neurology & neurosurgery
Abstract

Many medical (and ecological) processes involve the change of shape, whereby one trajectory changes into another trajectory at a specific time point. There has been little investigation into the study design needed to investigate these models. We consider the class of fixed effect change-point models with an underlying shape comprised two joined linear segments, also known as broken-stick models. We extend this model to include two sub-groups with different trajectories at the change-point, a change and no change class, and also include a missingness model to account for individuals with incomplete follow-up. Through a simulation study, we consider the relationship of sample size to the estimates of the underlying shape, the existence of a change-point, and the classification-error of sub-group labels. We use a Bayesian framework to account for the missing labels, and the analysis of each simulation is performed using standard Markov chain Monte Carlo techniques. Our simulation study is inspired by cognitive decline as measured by the Mini-Mental State Examination, where our extended model is appropriate due to the commonly observed mixture of individuals within studies who do or do not exhibit accelerated decline. We find that even for studies of modest size ( n = 500, with 50 individuals observed past the change-point) in the fixed effect setting, a change-point can be detected and reliably estimated across a range of observation-errors., This work was supported by the Medical Research Council (Unit Programme number U105292687).

Published
2016
Full Text
View/download PDF

9. Adult Lifespan Cognitive Variability in the Cross-Sectional Cam-CAN Cohort

Author

Fiona Matthews, Tim Dalgleish, Emma Green, James Rowe, Tibor Auer, Richard Henson, Carol Brayne, Simon White, Rhodri Cusack, Green, Emma [0000-0002-8687-5590], Matthews, Fiona [0000-0002-1728-2388], White, Simon [0000-0001-8642-7037], and Apollo - University of Cambridge Repository

Subjects
Gerontology, Adult, Male, ceiling effects, Adolescent, Health, Toxicology and Mutagenesis, cognitive variability, lcsh:Medicine, MMSE, Article, Cohort Studies, Young Adult, Cognition, Memory, Humans, Psychological testing, Effects of sleep deprivation on cognitive performance, Young adult, Episodic memory, Aged, Aged, 80 and over, Psychological Tests, lcsh:R, Public Health, Environmental and Occupational Health, verbal fluency, Confounding Factors, Epidemiologic, episodic memory, Middle Aged, Cross-Sectional Studies, Cognitive Aging, adult lifespan, heterogeneity, variance confounders, Cohort, Ceiling effect, Female, Psychology, Cognition Disorders, Cohort study
Abstract

This study examines variability across the age span in cognitive performance in a cross-sectional, population-based, adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study (n = 2680). A key question we highlight is whether using measures that are designed to detect age-related cognitive pathology may not be sensitive to, or reflective of, individual variability among younger adults. We present three issues that contribute to the debate for and against age-related increases in variability. Firstly, the need to formally define measures of central tendency and measures of variability. Secondly, in addition to the commonly addressed location-confounding (adjusting for covariates) there may exist changes in measures of variability due to confounder sub-groups. Finally, that increases in spread may be a result of floor or ceiling effects, where the measure is not sensitive enough at all ages. From the Cam-CAN study, a large population-based dataset, we demonstrate the existence of variability-confounding for the immediate episodic memory task, and show that increasing variance with age in our general cognitive measures is driven by a ceiling effect in younger age groups.

Published
2015

10. A Network Neuroscience Approach to Typical and Atypical Brain Development

Author

Sarah E. Morgan, Petra E. Vértes, Edward T. Bullmore, Simon R. White, Morgan, Sarah [0000-0002-1261-5884], White, Simon [0000-0001-8642-7037], Bullmore, Edward [0000-0002-8955-8283], Vertes, Petra [0000-0002-0992-3210], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Brain development, Nerve net, Autism Spectrum Disorder, Cognitive Neuroscience, Brain Structure and Function, Network neuroscience, Neuroimaging, Development, Article, 03 medical and health sciences, 0302 clinical medicine, medicine, ADHD, Humans, Radiology, Nuclear Medicine and imaging, Biological Psychiatry, FOS: Clinical medicine, Neurosciences, Brain, Human brain, medicine.disease, 030104 developmental biology, medicine.anatomical_structure, Autism spectrum disorder, Schizophrenia, Attention Deficit Disorder with Hyperactivity, Autism, Neurology (clinical), Nerve Net, Psychology, Neuroscience, 030217 neurology & neurosurgery, MRI
Abstract

Human brain networks based on neuroimaging data have already proven useful in characterizing both normal and abnormal brain structure and function. However, many brain disorders are neurodevelopmental in origin, highlighting the need to go beyond characterizing brain organization in terms of static networks. Here, we review the fast-growing literature shedding light on developmental changes in network phenotypes. We begin with an overview of recent large-scale efforts to map healthy brain development, and we describe the key role played by longitudinal data including repeated measurements over a long period of follow-up. We also discuss the subtle ways in which healthy brain network development can inform our understanding of disorders, including work bridging the gap between macroscopic neuroimaging results and the microscopic level. Finally, we turn to studies of three specific neurodevelopmental disorders that first manifest primarily in childhood and adolescence/early adulthood, namely psychotic disorders, attention-deficit/hyperactivity disorder, and autism spectrum disorder. In each case we discuss recent progress in understanding the atypical features of brain network development associated with the disorder, and we conclude the review with some suggestions for future directions.

Published
2018

11. Biased sampling activity: an investigation to promote discussion

Author

White, Simon R, Bonnett, Laura J, White, Simon [0000-0001-8642-7037], and Apollo - University of Cambridge Repository

Subjects
Practical activity, Biased sampling, Teaching, Original Article, Original Articles, Sampling, Teaching statistics
Abstract

Summary The statistical concept of sampling is often given little direct attention, typically reduced to the mantra “take a random sample”. This low resource and adaptable activity demonstrates sampling and explores issues that arise due to biased sampling.

Published
2018
Full Text
View/download PDF

12. May the odds be ever in your favour

Author

Bonnett, Laura J, White, Simon R, White, Simon [0000-0001-8642-7037], and Apollo - University of Cambridge Repository

Subjects
two-dice experiment, probabilities, simulations, practical activity, Teaching statistics
Abstract

Probability and chance are essential concepts, not just in statistics but in real life. We present an adaptable activity which investigates what we mean by bias, how we can identify bias, and how we can use it to our advantage!

Published
2018
Full Text
View/download PDF

13. Clinical services for adults with an intellectual disability and epilepsy: A comparison of management alternatives

Author

Adam P. Wagner, Simon R. White, Naomi Bateman, Tim Croudace, Marcus Redley, Howard Ring, Elizabeth Prince, Mark Pennington, White, Simon [0000-0001-8642-7037], Redley, Marcus [0000-0001-8866-7990], and Apollo - University of Cambridge Repository

Subjects
Gerontology, Male, 030506 rehabilitation, Health Care Providers, Nurses, Social Sciences, Cohort Studies, Cognition, 0302 clinical medicine, Intellectual disability, Medicine and Health Sciences, Psychology, Public and Occupational Health, Independent research, Multidisciplinary, Pharmaceutics, Learning Disabilities, Health services research, Middle Aged, Professions, Patient benefit, Neurology, Medicine, Female, Health Services Research, 0305 other medical science, Research Article, Neurological Drug Therapy, Adult, Adolescent, Disabilities, Cognitive Neuroscience, Science, Decision Making, Library science, 03 medical and health sciences, Young Adult, Quality of life (healthcare), Drug Therapy, Intellectual Disability, medicine, Humans, Epilepsy, business.industry, Cognitive Psychology, Biology and Life Sciences, medicine.disease, Health Care, People and Places, Quality of Life, Cognitive Science, Population Groupings, business, 030217 neurology & neurosurgery, Neuroscience
Abstract

BackgroundIntellectual disability (ID) is relatively common in people with epilepsy, with prevalence estimated to be around 25%. Surprisingly, given this relatively high frequency, along with higher rates of refractory epilepsy than in those without ID, little is known about outcomes of different management approaches/clinical services treating epilepsy in adults with ID-we investigate this area.Materials & methodsWe undertook a naturalistic observational cohort study measuring outcomes in n = 91 adults with ID over a 7-month period (recruited within the period March 2008 to April 2010). Participants were receiving treatment for refractory epilepsy (primarily) in one of two clinical service settings: community ID teams (CIDTs) or hospital Neurology services.ResultsThe pattern of comorbidities appeared important in predicting clinical service, with Neurologists managing the epilepsy of relatively more of those with neurological comorbidities whilst CIDTs managed the epilepsy of relatively more of those with psychiatric comorbidities. Epilepsy-related outcomes, as measured by the Glasgow Epilepsy Outcome Scale 35 (GEOS-35) and the Epilepsy and Learning Disabilities Quality of Life Scale (ELDQoL) did not differ significantly between Neurology services and CIDTs.DiscussionIn the context of this study, the absence of evidence for differences in epilepsy-related outcomes amongst adults with ID and refractory epilepsy between mainstream neurology and specialist ID clinical services is considered. Determining the selection of the service managing the epilepsy of adults with an ID on the basis of the skill sets also required to treat associated comorbidities may hence be a reasonable heuristic.

Published
2017
Full Text
View/download PDF

14. Prognostic models for identifying adults with intellectual disabilities and mealtime support needs who are at greatest risk of respiratory infection and emergency hospitalisation

Author

Perez, C.M., Wagner, A.P., Ball, S.L., White, S.R., Clare, I.C.H., Holland, A.J., Redley, M., White, Simon [0000-0001-8642-7037], Clare, Isabel [0000-0002-5385-008X], Holland, Anthony [0000-0003-4107-130X], Redley, Marcus [0000-0001-8866-7990], and Apollo - University of Cambridge Repository

Subjects
hospital admissions, dysphagia, intellectual disability, physical health, social care, respiratory illness
Abstract

$\textbf{Background}$ Among adults with intellectual disabilities (ID), problems with eating, drinking and swallowing (EDS), and an associated need for mealtime support, are common, with an estimated 15% of adults known to specialist ID services requiring mealtime support. We set out to identify which adults with ID who receive mealtime support are at an increased risk of $\textit{respiratory infections}$ and $\textit{emergency hospitalisation related to EDS problems}$. $\textbf{Method}$ An exploratory, prospective cohort study was undertaken in the East of England. At baseline, structured interviews with the caregivers of 142 adults with ID and any type of mealtime support needs were used to gather information on health and support needs over the previous 12 months. These interviews were repeated at follow-up, 12 months later. The resulting dataset, covering a 24-month period, was analysed with logistic regression, using model averaging to perform sensitivity analysis, and backwards step-wise variable selection to identify the most important predictors. $\textbf{Results}$ Individuals with $\textit{a history of respiratory infections}$ (in the first year of study), those who had $\textit{epilepsy}$ and those with $\textit{caregiver-reported difficulty swallowing}$ were most likely to have $\textit{respiratory infections}$ in the second year. Adults with $\textit{increasing mealtime support needs, epilepsy}$ and/or $\textit{full mealtime support needs}$ (fed mainly or entirely by a caregiver or enterally) were at increased risk of $\textit{emergency hospitalisation}$ for EDS-related problems. $\textbf{Conclusions}$ Our findings highlight the importance of carefully monitoring health issues experienced by adults with ID and EDS problems, as well as their eating, drinking and swallowing skills. However, the models developed in this exploratory research require validation through future studies addressing the EDS problems commonly experienced by adults with ID and their implications for health outcomes and quality of life. Further research into the relationship between epilepsy and EDS problems would provide much-needed insight into the complex relationship between the two areas.

Published
2017
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results