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1. The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

Author

Di Martino, A, Yan, C-G, Li, Q, Denio, E, Castellanos, FX, Alaerts, K, Anderson, JS, Assaf, M, Bookheimer, SY, Dapretto, M, Deen, B, Delmonte, S, Dinstein, I, Ertl-Wagner, B, Fair, DA, Gallagher, L, Kennedy, DP, Keown, CL, Keysers, C, Lainhart, JE, Lord, C, Luna, B, Menon, V, Minshew, NJ, Monk, CS, Mueller, S, Müller, R-A, Nebel, MB, Nigg, JT, O'Hearn, K, Pelphrey, KA, Peltier, SJ, Rudie, JD, Sunaert, S, Thioux, M, Tyszka, JM, Uddin, LQ, Verhoeven, JS, Wenderoth, N, Wiggins, JL, Mostofsky, SH, and Milham, MP

Subjects
Mental Health, Brain Disorders, Biomedical Imaging, Neurosciences, Behavioral and Social Science, Basic Behavioral and Social Science, Intellectual and Developmental Disabilities (IDD), Clinical Research, Autism, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Adolescent, Adult, Brain, Brain Mapping, Child, Child Development Disorders, Pervasive, Connectome, Humans, Information Dissemination, Internet, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Neuroimaging, Phenotype, Signal Processing, Computer-Assisted, Young Adult, data sharing, default network, interhemispheric connectivity, intrinsic functional connectivity, resting-state fMRI, thalamus, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

Published
2014

3. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Author

Hoogman, M., Rooij, D. van, Klein, M., Boedhoe, P., Ilioska, I., Li, T., Patel, Y., Postema, M.C., Zhang-James, Y., Anagnostou, E., Arango, C., Auzias, G., Banaschewski, T., Bau, C.H.D., Behrmann, M., Bellgrove, Mark A., Brandeis, D., Brem, S., Busatto, G.F., Calderoni, S., Calvo, R., Castellanos, F.X., Coghill, D., Conzelmann, A., Daly, E., Deruelle, C., Dinstein, I., Durston, S., Ecker, C., Ehrlich, S., Epstein, J.N., Fair, D.A., Fitzgerald, J., Freitag, C.M., Frodl, T., Gallagher, L., Grevet, E.H., Haavik, J., Hoekstra, P.J., Janssen, J., Karkashadze, G., King, J.A., Konrad, K., Kuntsi, J., Lazaro, L., Lerch, J.P., Lesch, K.P., Louza, M.R., Luna, B., Mattos, P., McGrath, J., Muratori, F., Murphy, C., Nigg, J.T., Oberwelland-Weiss, E., Tuura, R.L. O'Gorman, O'Hearn, K., Oosterlaan, J., Parellada, M., Pauli, P., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Retico, A., Rosa, P.G., Rubia, K., Shaw, P., Silk, T.J., Tamm, L., Vilarroya, O., Walitza, S., Jahanshad, N., Faraone, S.V, Francks, C., Heuvel, O.A. van den, Paus, T., Thompson, P.M., Buitelaar, J.K., Franke, B., Hoogman, M., Rooij, D. van, Klein, M., Boedhoe, P., Ilioska, I., Li, T., Patel, Y., Postema, M.C., Zhang-James, Y., Anagnostou, E., Arango, C., Auzias, G., Banaschewski, T., Bau, C.H.D., Behrmann, M., Bellgrove, Mark A., Brandeis, D., Brem, S., Busatto, G.F., Calderoni, S., Calvo, R., Castellanos, F.X., Coghill, D., Conzelmann, A., Daly, E., Deruelle, C., Dinstein, I., Durston, S., Ecker, C., Ehrlich, S., Epstein, J.N., Fair, D.A., Fitzgerald, J., Freitag, C.M., Frodl, T., Gallagher, L., Grevet, E.H., Haavik, J., Hoekstra, P.J., Janssen, J., Karkashadze, G., King, J.A., Konrad, K., Kuntsi, J., Lazaro, L., Lerch, J.P., Lesch, K.P., Louza, M.R., Luna, B., Mattos, P., McGrath, J., Muratori, F., Murphy, C., Nigg, J.T., Oberwelland-Weiss, E., Tuura, R.L. O'Gorman, O'Hearn, K., Oosterlaan, J., Parellada, M., Pauli, P., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Retico, A., Rosa, P.G., Rubia, K., Shaw, P., Silk, T.J., Tamm, L., Vilarroya, O., Walitza, S., Jahanshad, N., Faraone, S.V, Francks, C., Heuvel, O.A. van den, Paus, T., Thompson, P.M., Buitelaar, J.K., and Franke, B.

Abstract

Contains fulltext : 248364.pdf (Publisher’s version ) (Open Access), Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Published
2022

4. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Author

Hoogman, M, van Rooij, D, Klein, M, Boedhoe, P, Ilioska, I, Li, T, Patel, Y, Postema, MC, Zhang-James, Y, Anagnostou, E, Arango, C, Auzias, G, Banaschewski, T, Bau, CHD, Behrmann, M, Bellgrove, MA, Brandeis, D, Brem, S, Busatto, GF, Calderoni, S, Calvo, R, Castellanos, FX, Coghill, D, Conzelmann, A, Daly, E, Deruelle, C, Dinstein, I, Durston, S, Ecker, C, Ehrlich, S, Epstein, JN, Fair, DA, Fitzgerald, J, Freitag, CM, Frodl, T, Gallagher, L, Grevet, EH, Haavik, J, Hoekstra, PJ, Janssen, J, Karkashadze, G, King, JA, Konrad, K, Kuntsi, J, Lazaro, L, Lerch, JP, Lesch, K-P, Louza, MR, Luna, B, Mattos, P, McGrath, J, Muratori, F, Murphy, C, Nigg, JT, Oberwelland-Weiss, E, Tuura, RLO, O'Hearn, K, Oosterlaan, J, Parellada, M, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Shaw, P, Silk, TJ, Tamm, L, Vilarroya, O, Walitza, S, Jahanshad, N, Faraone, S, Francks, C, van den Heuvel, OA, Paus, T, Thompson, PM, Buitelaar, JK, Franke, B, Hoogman, M, van Rooij, D, Klein, M, Boedhoe, P, Ilioska, I, Li, T, Patel, Y, Postema, MC, Zhang-James, Y, Anagnostou, E, Arango, C, Auzias, G, Banaschewski, T, Bau, CHD, Behrmann, M, Bellgrove, MA, Brandeis, D, Brem, S, Busatto, GF, Calderoni, S, Calvo, R, Castellanos, FX, Coghill, D, Conzelmann, A, Daly, E, Deruelle, C, Dinstein, I, Durston, S, Ecker, C, Ehrlich, S, Epstein, JN, Fair, DA, Fitzgerald, J, Freitag, CM, Frodl, T, Gallagher, L, Grevet, EH, Haavik, J, Hoekstra, PJ, Janssen, J, Karkashadze, G, King, JA, Konrad, K, Kuntsi, J, Lazaro, L, Lerch, JP, Lesch, K-P, Louza, MR, Luna, B, Mattos, P, McGrath, J, Muratori, F, Murphy, C, Nigg, JT, Oberwelland-Weiss, E, Tuura, RLO, O'Hearn, K, Oosterlaan, J, Parellada, M, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Shaw, P, Silk, TJ, Tamm, L, Vilarroya, O, Walitza, S, Jahanshad, N, Faraone, S, Francks, C, van den Heuvel, OA, Paus, T, Thompson, PM, Buitelaar, JK, and Franke, B

Abstract

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Published
2022

7. Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: Findings from the ENIGMA ADHD, ASD, and OCD Working Groups

Author

Boedhoe, P.S., Rooij, D. van, Hoogman, M., Twisk, J.W.R., Schmaal, L., Abe, Y., Alonso, P., Ameis, S.H., Anikin, A., Anticevic, A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Banaschewski, T., Baranov, A., Batistuzzo, M.C., Baumeister, S., Baur-Streubel, R., Behrmann, M., Bellgrove, M.A., Benedetti, F. De, Beucke, J.C., Biederman, J., Bollettini, I., Bose, A., Bralten, J., Bramati, I.E., Brandeis, D., Brem, S., Brennan, B.P., Busatto, G.F., Calderoni, S., Calvo, A., Calvo, R., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Cheng, Y., Cho, K.I.K., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Dale, A.M., Dallaspezia, S., Daly, E., Denys, D., Deruelle, C., Martino, A, Dinstein, I., Doyle, A.E., Durston, S., Earl, E.A., Ecker, C., Ehrlich, S., Ely, B.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Fedor, J., Feng, X., Feusner, J.D., Fitzgerald, J., Fitzgerald, K.D., Fouche, J.P., Freitag, C.M., Fridgeirsson, E.A., Frodl, T., Gabel, M.C., Gallagher, L., Gogberashvili, T., Gori, I., Gruner, P., Gürsel, D.A., Haar, S., Haavik, J., Hall, G.B., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hirano, Y., Hoekstra, P.J., Hoexter, M.Q., Hohmann, S., Høvik, M.F., Hu, H., Huyser, C., Jahanshad, N., Jalbrzikowski, M., James, A., Janssen, J, Jaspers-Fayer, F., Jernigan, T.L., Kapilushniy, D., Kardatzki, B., Buitelaar, J.K., Franke, B., Heuvel, O.A. van den, Boedhoe, P.S., Rooij, D. van, Hoogman, M., Twisk, J.W.R., Schmaal, L., Abe, Y., Alonso, P., Ameis, S.H., Anikin, A., Anticevic, A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Banaschewski, T., Baranov, A., Batistuzzo, M.C., Baumeister, S., Baur-Streubel, R., Behrmann, M., Bellgrove, M.A., Benedetti, F. De, Beucke, J.C., Biederman, J., Bollettini, I., Bose, A., Bralten, J., Bramati, I.E., Brandeis, D., Brem, S., Brennan, B.P., Busatto, G.F., Calderoni, S., Calvo, A., Calvo, R., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Cheng, Y., Cho, K.I.K., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Dale, A.M., Dallaspezia, S., Daly, E., Denys, D., Deruelle, C., Martino, A, Dinstein, I., Doyle, A.E., Durston, S., Earl, E.A., Ecker, C., Ehrlich, S., Ely, B.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Fedor, J., Feng, X., Feusner, J.D., Fitzgerald, J., Fitzgerald, K.D., Fouche, J.P., Freitag, C.M., Fridgeirsson, E.A., Frodl, T., Gabel, M.C., Gallagher, L., Gogberashvili, T., Gori, I., Gruner, P., Gürsel, D.A., Haar, S., Haavik, J., Hall, G.B., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hirano, Y., Hoekstra, P.J., Hoexter, M.Q., Hohmann, S., Høvik, M.F., Hu, H., Huyser, C., Jahanshad, N., Jalbrzikowski, M., James, A., Janssen, J, Jaspers-Fayer, F., Jernigan, T.L., Kapilushniy, D., Kardatzki, B., Buitelaar, J.K., Franke, B., and Heuvel, O.A. van den

Abstract

Contains fulltext : 225388.pdf (Publisher’s version ) (Closed access), OBJECTIVE: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. METHODS: Structural T(1)-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). RESULTS: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. CONCLUSIONS: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Published
2020

8. Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

Author

Boedhoe, PSW, van Rooij, D, Hoogman, M, Twisk, JWR, Schmaal, L, Abe, Y, Alonso, P, Ameis, SH, Anikin, A, Anticevic, A, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Banaschewski, T, Baranov, A, Batistuzzo, MC, Baumeister, S, Baur-Streubel, R, Behrmann, M, Bellgrove, MA, Benedetti, F, Beucke, JC, Biederman, J, Bollettini, I, Bose, A, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Brennan, BP, Busatto, GF, Calderoni, S, Calvo, A, Calvo, R, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Cheng, Y, Cho, KIK, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, A, Dale, AM, Dallaspezia, S, Daly, E, Denys, D, Deruelle, C, Di Martino, A, Dinstein, I, Doyle, AE, Durston, S, Earl, EA, Ecker, C, Ehrlich, S, Ely, BA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, S, Fedor, J, Feng, X, Feusner, JD, Fitzgerald, J, Fitzgerald, KD, Fouche, J-P, Freitag, CM, Fridgeirsson, EA, Frodl, T, Gabel, MC, Gallagher, L, Gogberashvili, T, Gori, I, Gruner, P, Gursel, DA, Haar, S, Haavik, J, Hall, GB, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hirano, Y, Hoekstra, PJ, Hoexter, MQ, Hohmann, S, Hovik, MF, Hu, H, Huyser, C, Jahanshad, N, Jalbrzikowski, M, James, A, Janssen, J, Jaspers-Fayer, F, Jernigan, TL, Kapilushniy, D, Kardatzki, B, Karkashadze, G, Kathmann, N, Kaufmann, C, Kelly, C, Khadka, S, King, JA, Koch, K, Kohls, G, Konrad, K, Kuno, M, Kuntsi, J, Kvale, G, Kwon, JS, Lazaro, L, Lera-Miguel, S, Lesch, K-P, Hoekstra, L, Liu, Y, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, Malpas, CB, Marques, P, Marsh, R, Martinez-Zalacain, I, Mataix-Cols, D, Mattos, P, McCarthy, H, McGrath, J, Mehta, MA, Menchon, JM, Mennes, M, Martinho, MM, Moreira, PS, Morer, A, Morgado, P, Muratori, F, Murphy, CM, Murphy, DGM, Nakagawa, A, Nakamae, T, Nakao, T, Namazova-Baranova, L, Narayanaswamy, JC, Nicolau, R, Nigg, JT, Novotny, SE, Nurmi, EL, Weiss, EO, Tuura, RLO, O'Hearn, K, O'Neill, J, Oosterlaan, J, Oranje, B, Paloyelis, Y, Parellada, M, Pauli, P, Perriello, C, Piacentini, J, Piras, F, Plessen, KJ, Puig, O, Ramos-Quiroga, JA, Reddy, YCJ, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Rus, OG, Sakai, Y, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Shook, D, Silk, TJ, Simpson, HB, Skokauskas, N, Vila, JCS, Solovieva, A, Soreni, N, Soriano-Mas, C, Spalletta, G, Stern, ER, Stevens, MC, Stewart, SE, Sudre, G, Szeszko, PR, Tamm, L, Taylor, MJ, Tolin, DF, Tosetti, M, Tovar-Moll, F, Tsuchiyagaito, A, van Erp, TGM, van Wingen, GA, Vance, A, Venkatasubramanian, G, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Wallace, GL, Wang, Z, Wolfers, T, Yoncheva, YN, Yun, J-Y, Zanetti, M, Zhou, F, Ziegler, GC, Zierhut, KC, Zwiers, MP, Thompson, PM, Stein, DJ, Buitelaar, J, Franke, B, van den Heuvel, OA, Boedhoe, PSW, van Rooij, D, Hoogman, M, Twisk, JWR, Schmaal, L, Abe, Y, Alonso, P, Ameis, SH, Anikin, A, Anticevic, A, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Banaschewski, T, Baranov, A, Batistuzzo, MC, Baumeister, S, Baur-Streubel, R, Behrmann, M, Bellgrove, MA, Benedetti, F, Beucke, JC, Biederman, J, Bollettini, I, Bose, A, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Brennan, BP, Busatto, GF, Calderoni, S, Calvo, A, Calvo, R, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Cheng, Y, Cho, KIK, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, A, Dale, AM, Dallaspezia, S, Daly, E, Denys, D, Deruelle, C, Di Martino, A, Dinstein, I, Doyle, AE, Durston, S, Earl, EA, Ecker, C, Ehrlich, S, Ely, BA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, S, Fedor, J, Feng, X, Feusner, JD, Fitzgerald, J, Fitzgerald, KD, Fouche, J-P, Freitag, CM, Fridgeirsson, EA, Frodl, T, Gabel, MC, Gallagher, L, Gogberashvili, T, Gori, I, Gruner, P, Gursel, DA, Haar, S, Haavik, J, Hall, GB, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hirano, Y, Hoekstra, PJ, Hoexter, MQ, Hohmann, S, Hovik, MF, Hu, H, Huyser, C, Jahanshad, N, Jalbrzikowski, M, James, A, Janssen, J, Jaspers-Fayer, F, Jernigan, TL, Kapilushniy, D, Kardatzki, B, Karkashadze, G, Kathmann, N, Kaufmann, C, Kelly, C, Khadka, S, King, JA, Koch, K, Kohls, G, Konrad, K, Kuno, M, Kuntsi, J, Kvale, G, Kwon, JS, Lazaro, L, Lera-Miguel, S, Lesch, K-P, Hoekstra, L, Liu, Y, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, Malpas, CB, Marques, P, Marsh, R, Martinez-Zalacain, I, Mataix-Cols, D, Mattos, P, McCarthy, H, McGrath, J, Mehta, MA, Menchon, JM, Mennes, M, Martinho, MM, Moreira, PS, Morer, A, Morgado, P, Muratori, F, Murphy, CM, Murphy, DGM, Nakagawa, A, Nakamae, T, Nakao, T, Namazova-Baranova, L, Narayanaswamy, JC, Nicolau, R, Nigg, JT, Novotny, SE, Nurmi, EL, Weiss, EO, Tuura, RLO, O'Hearn, K, O'Neill, J, Oosterlaan, J, Oranje, B, Paloyelis, Y, Parellada, M, Pauli, P, Perriello, C, Piacentini, J, Piras, F, Plessen, KJ, Puig, O, Ramos-Quiroga, JA, Reddy, YCJ, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Rus, OG, Sakai, Y, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Shook, D, Silk, TJ, Simpson, HB, Skokauskas, N, Vila, JCS, Solovieva, A, Soreni, N, Soriano-Mas, C, Spalletta, G, Stern, ER, Stevens, MC, Stewart, SE, Sudre, G, Szeszko, PR, Tamm, L, Taylor, MJ, Tolin, DF, Tosetti, M, Tovar-Moll, F, Tsuchiyagaito, A, van Erp, TGM, van Wingen, GA, Vance, A, Venkatasubramanian, G, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Wallace, GL, Wang, Z, Wolfers, T, Yoncheva, YN, Yun, J-Y, Zanetti, M, Zhou, F, Ziegler, GC, Zierhut, KC, Zwiers, MP, Thompson, PM, Stein, DJ, Buitelaar, J, Franke, B, and van den Heuvel, OA

Abstract

Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. Methods: Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Published
2020

10. Cortical and Subcortical Brain Morphometry Differences Between Patients With Autism Spectrum Disorder and Healthy Individuals Across the Lifespan: Results From the ENIGMA ASD Working Group

Author

Rooij, D. van, Anagnostou, E., Arango, C., Auzias, G., Behrmann, M., Busatto, G.F., Calderoni, S., Daly, E., Deruelle, C., Martino, A, Dinstein, I., Duran, F.L.S., Durston, S., Ecker, C., Fair, D., Fedor, J., Fitzgerald, J., Freitag, C.M., Gallagher, L., Gori, I., Haar, S., Hoekstra, L., Jahanshad, N., Jalbrzikowski, M., Janssen, J, Lerch, J., Luna, B., Martinho, M.M., McGrath, J., Muratori, F., Murphy, C.M., Murphy, D.G.M., O'Hearn, K., Oranje, B., Parellada, M., Retico, A., Rosa, P., Rubia, K., Shook, D., Taylor, M., Thompson, P.M., Tosetti, M., Wallace, G.L., Zhou, F., Buitelaar, J.K., Rooij, D. van, Anagnostou, E., Arango, C., Auzias, G., Behrmann, M., Busatto, G.F., Calderoni, S., Daly, E., Deruelle, C., Martino, A, Dinstein, I., Duran, F.L.S., Durston, S., Ecker, C., Fair, D., Fedor, J., Fitzgerald, J., Freitag, C.M., Gallagher, L., Gori, I., Haar, S., Hoekstra, L., Jahanshad, N., Jalbrzikowski, M., Janssen, J, Lerch, J., Luna, B., Martinho, M.M., McGrath, J., Muratori, F., Murphy, C.M., Murphy, D.G.M., O'Hearn, K., Oranje, B., Parellada, M., Retico, A., Rosa, P., Rubia, K., Shook, D., Taylor, M., Thompson, P.M., Tosetti, M., Wallace, G.L., Zhou, F., and Buitelaar, J.K.

Abstract

Item does not contain fulltext, OBJECTIVE: Neuroimaging studies show structural differences in both cortical and subcortical brain regions in children and adults with autism spectrum disorder (ASD) compared with healthy subjects. Findings are inconsistent, however, and it is unclear how differences develop across the lifespan. The authors investigated brain morphometry differences between individuals with ASD and healthy subjects, cross-sectionally across the lifespan, in a large multinational sample from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) ASD working group. METHOD: The sample comprised 1,571 patients with ASD and 1,651 healthy control subjects (age range, 2-64 years) from 49 participating sites. MRI scans were preprocessed at individual sites with a harmonized protocol based on a validated automated-segmentation software program. Mega-analyses were used to test for case-control differences in subcortical volumes, cortical thickness, and surface area. Development of brain morphometry over the lifespan was modeled using a fractional polynomial approach. RESULTS: The case-control mega-analysis demonstrated that ASD was associated with smaller subcortical volumes of the pallidum, putamen, amygdala, and nucleus accumbens (effect sizes [Cohen's d], 0.13 to -0.13), as well as increased cortical thickness in the frontal cortex and decreased thickness in the temporal cortex (effect sizes, -0.21 to 0.20). Analyses of age effects indicate that the development of cortical thickness is altered in ASD, with the largest differences occurring around adolescence. No age-by-ASD interactions were observed in the subcortical partitions. CONCLUSIONS: The ENIGMA ASD working group provides the largest study of brain morphometry differences in ASD to date, using a well-established, validated, publicly available analysis pipeline. ASD patients showed altered morphometry in the cognitive and affective parts of the striatum, frontal cortex, and temporal cortex. Complex developmental trajecto

Published
2018

11. The Negev hospital-university-based (HUB) database of autism

Author

Menashe, I., primary, Dinstein, I., additional, Michaelovski, A., additional, Fluser, H., additional, Ilan, M., additional, Faroy, M., additional, Bar-Sinai, A., additional, Doitch, S., additional, Cohen, M., additional, Davidovitch, N., additional, Golan, H., additional, Arbel, S., additional, and Meiri, G., additional

Published
2017
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14. The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

Author

Di Martino, A, primary, Yan, C-G, additional, Li, Q, additional, Denio, E, additional, Castellanos, F X, additional, Alaerts, K, additional, Anderson, J S, additional, Assaf, M, additional, Bookheimer, S Y, additional, Dapretto, M, additional, Deen, B, additional, Delmonte, S, additional, Dinstein, I, additional, Ertl-Wagner, B, additional, Fair, D A, additional, Gallagher, L, additional, Kennedy, D P, additional, Keown, C L, additional, Keysers, C, additional, Lainhart, J E, additional, Lord, C, additional, Luna, B, additional, Menon, V, additional, Minshew, N J, additional, Monk, C S, additional, Mueller, S, additional, Müller, R-A, additional, Nebel, M B, additional, Nigg, J T, additional, O'Hearn, K, additional, Pelphrey, K A, additional, Peltier, S J, additional, Rudie, J D, additional, Sunaert, S, additional, Thioux, M, additional, Tyszka, J M, additional, Uddin, L Q, additional, Verhoeven, J S, additional, Wenderoth, N, additional, Wiggins, J L, additional, Mostofsky, S H, additional, and Milham, M P, additional

Published
2013
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17. An iterative clustering procedure

Author

Dinstein, I and Haralick, R. M

Subjects
Computers
Abstract

Iterative clustering technique for minimizing probability of differences between binary data reconstructions from cluster codes and initial data

Published
1971

18. Textural features for image classification

Author

Haralick, R. M, Dinstein, I, and Shanmugam, K

Subjects
Instrumentation And Photography
Abstract

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

Published
1973

38. Walsh descriptors for shape discrimination.

Author

Dinstein, I. and Silberberg, T.

Subjects
*SIGNAL theory, *POWER spectra, *ALGORITHMS
Abstract

A shift invariant Walsh power spectrum for real periodic signals is defined, and an algorithm for its computation is presented. The Walsh power spectrum of the boundary angular function φ of Zahn and Roskies (1972) is computed. It is shown that most of the energy of the power spectrum is concentrated in the lower sequency coefficients. A small number of low-sequency coefficients is enough for shape discrimination of closed contours. [ABSTRACT FROM AUTHOR]

Published
1980
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43. Prediction of effects of weather on image quality: preliminary results of model validation

Author

Dinstein, I., Zoabi, H., and Kopeika, N. S.

Abstract

Using the atmospheric modulation transfer function area (MTFA) as a single-valued numerical criterion for image quality horizontally near the ground propagated through the atmosphere, a statistical study of atmospheric imaging data accumulated over a three-year period has led to the determination of regression coefficients with which to quantitatively predict image quality as a function of wavelength, over the 400–1000-nm wavelength region, according to weather forecast. Utilization of this procedure is simple: one plugs in expected values for wind speed, air temperature, and relative humidity in the regression coefficient expression for MTFA. The larger the expected MTFA, the better the expected image quality. Two sets of regression coefficient data have been obtained, one each for desert and nondesert climates, corresponding to summer and winter data here. Preliminary experimentation over a different line of sight indicates that the accuracy of the prediction is fairly reliable.

Published
1988

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