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1. White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

Author

Kim, Bo-Gyeom, Kim, Gakyung, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargalló, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolín, Sara, Beucke, Jan Carl, Bollettini, Irene, Brem, Silvia, Brennan, Brian P., Buitelaar, Jan K., Calvo, Rosa, Castelo-Branco, Miguel, Cheng, Yuqi, Chhatkuli, Ritu Bhusal, Ciullo, Valentina, Coelho, Ana, Couto, Beatriz, Dallaspezia, Sara, Ely, Benjamin A., Ferreira, Sónia, Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael, Gruner, Patricia, Hagen, Kristen, Hansen, Bjarne, Hanna, Gregory L., Hirano, Yoshiyuki, Höxter, Marcelo Q., Hough, Morgan, Hu, Hao, Huyser, Chaim, Ikuta, Toshikazu, Jahanshad, Neda, James, Anthony, Jaspers-Fayer, Fern, Kasprzak, Selina, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Lee, Junhee, Lochner, Christine, Lu, Jin, Manrique, Daniela Rodriguez, Martínez-Zalacaín, Ignacio, Masuda, Yoshitada, Matsumoto, Koji, Maziero, Maria Paula, Menchón, Jose M., Minuzzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Narayanaswamy, Janardhanan C., Narumoto, Jin, Ortiz, Ana E., Ota, Junko, Pariente, Jose C., Perriello, Chris, Picó-Pérez, Maria, Pittenger, Christopher, Poletti, Sara, Real, Eva, Reddy, Y. C. Janardhan, van Rooij, Daan, Sakai, Yuki, Sato, João Ricardo, Segalas, Cinto, Shavitt, Roseli G., Shen, Zonglin, Shimizu, Eiji, Shivakumar, Venkataram, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Sousa, Mafalda Machado, Spalletta, Gianfranco, Stern, Emily R., Stewart, S. Evelyn, Szeszko, Philip R., Thomas, Rajat, Thomopoulos, Sophia I., Vecchio, Daniela, Venkatasubramanian, Ganesan, Vriend, Chris, Walitza, Susanne, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij, Xu, Jian, Yamada, Kei, Yun, Je-Yeon, Zarei, Mojtaba, Zhao, Qing, Zhu, Xi, Thompson, Paul M., Bruin, Willem B., van Wingen, Guido A., Piras, Federica, Piras, Fabrizio, Stein, Dan J., van den Heuvel, Odile A., Simpson, Helen Blair, Marsh, Rachel, and Cha, Jiook

Published
2024
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2. Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure

Author

Vriend, Chris, de Joode, Niels T., Pouwels, Petra J. W., Liu, Feng, Otaduy, Maria C. G., Pastorello, Bruno, Robertson, Frances C., Ipser, Jonathan, Lee, Seonjoo, Hezel, Dianne M., van Meter, Page E., Batistuzzo, Marcelo C., Hoexter, Marcelo Q., Sheshachala, Karthik, Narayanaswamy, Janardhanan C., Venkatasubramanian, Ganesan, Lochner, Christine, Miguel, Euripedes C., Reddy, Y. C. Janardhan, Shavitt, Roseli G., Stein, Dan J., Wall, Melanie, Simpson, Helen Blair, and van den Heuvel, Odile A.

Published
2024
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3. The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium.

Author

Bruin, Willem, Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea, Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo, Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan, Echevarria, Marco, Eng, Goi, Ferreira, Sónia, Feusner, Jamie, Grazioplene, Rachael, Gruner, Patricia, Guo, Joyce, Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo, Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun, Lazaro, Luisa, Li, Chiang-Shan, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose, Moreira, Pedro, Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan, Nurmi, Erika, Zorrilla, Jose, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan, Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair, Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily, Evelyn Stewart, S, Szeszko, Philip, Tang, Jinsong, Thomopoulos, Sophia, Thorsen, Anders, Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya, Venkatasubramanian, Ganesan, Vetter, Nora, Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke, van Marle, Hein, van de Mortel, Laurens, van der Straten, Anouk, van der Werf, Ysbrand, Thompson, Paul, Stein, Dan, van den Heuvel, Odile, van Wingen, Guido, and Piacentini, John

Subjects
Humans, Connectome, Brain Mapping, Magnetic Resonance Imaging, Brain, Obsessive-Compulsive Disorder, Biomarkers, Neural Pathways
Abstract

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohens d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohens d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Published
2023

4. Correction: White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

Author

Kim, Bo-Gyeom, Kim, Gakyung, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargalló, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolín, Sara, Beucke, Jan Carl, Bollettini, Irene, Brem, Silvia, Brennan, Brian P., Buitelaar, Jan K., Calvo, Rosa, Castelo-Branco, Miguel, Cheng, Yuqi, Chhatkuli, Ritu Bhusal, Ciullo, Valentina, Coelho, Ana, Couto, Beatriz, Dallaspezia, Sara, Ely, Benjamin A., Ferreira, Sónia, Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael, Gruner, Patricia, Hagen, Kristen, Hansen, Bjarne, Hanna, Gregory L., Hirano, Yoshiyuki, Höxter, Marcelo Q., Hough, Morgan, Hu, Hao, Huyser, Chaim, Ikuta, Toshikazu, Jahanshad, Neda, James, Anthony, Jaspers-Fayer, Fern, Kasprzak, Selina, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Lee, Junhee, Lochner, Christine, Lu, Jin, Manrique, Daniela Rodriguez, Martínez-Zalacaín, Ignacio, Masuda, Yoshitada, Matsumoto, Koji, Maziero, Maria Paula, Menchón, Jose M., Minuzzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Narayanaswamy, Janardhanan C., Narumoto, Jin, Ortiz, Ana E., Ota, Junko, Pariente, Jose C., Perriello, Chris, Picó-Pérez, Maria, Pittenger, Christopher, Poletti, Sara, Real, Eva, Reddy, Y. C. Janardhan, van Rooij, Daan, Sakai, Yuki, Sato, João Ricardo, Segalas, Cinto, Shavitt, Roseli G., Shen, Zonglin, Shimizu, Eiji, Shivakumar, Venkataram, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Sousa, Mafalda Machado, Spalletta, Gianfranco, Stern, Emily R., Stewart, S. Evelyn, Szeszko, Philip R., Thomas, Rajat, Thomopoulos, Sophia I., Vecchio, Daniela, Venkatasubramanian, Ganesan, Vriend, Chris, Walitza, Susanne, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij, Xu, Jian, Yamada, Kei, Yun, Je-Yeon, Zarei, Mojtaba, Zhao, Qing, Zhu, Xi, Thompson, Paul M., Bruin, Willem B., van Wingen, Guido A., Piras, Federica, Piras, Fabrizio, Stein, Dan J., van den Heuvel, Odile A., Simpson, Helen Blair, Marsh, Rachel, and Cha, Jiook

Published
2024
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7. An overview of the first 5 years of the ENIGMA obsessive–compulsive disorder working group: The power of worldwide collaboration

Author

van den Heuvel, Odile A, Boedhoe, Premika SW, Bertolin, Sara, Bruin, Willem B, Francks, Clyde, Ivanov, Iliyan, Jahanshad, Neda, Kong, Xiang‐Zhen, Kwon, Jun Soo, O'Neill, Joseph, Paus, Tomas, Patel, Yash, Piras, Fabrizio, Schmaal, Lianne, Soriano‐Mas, Carles, Spalletta, Gianfranco, van Wingen, Guido A, Yun, Je‐Yeon, Vriend, Chris, Simpson, H Blair, van Rooij, Daan, Hoexter, Marcelo Q, Hoogman, Martine, Buitelaar, Jan K, Arnold, Paul, Beucke, Jan C, Benedetti, Francesco, Bollettini, Irene, Bose, Anushree, Brennan, Brian P, De Nadai, Alessandro S, Fitzgerald, Kate, Gruner, Patricia, Grünblatt, Edna, Hirano, Yoshiyuki, Huyser, Chaim, James, Anthony, Koch, Kathrin, Kvale, Gerd, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Mataix‐Cols, David, Morgado, Pedro, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika, Pittenger, Christopher, Reddy, YC Janardhan, Sato, João R, Soreni, Noam, Stewart, S Evelyn, Taylor, Stephan F, Tolin, David, Thomopoulos, Sophia I, Veltman, Dick J, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Thompson, Paul M, Stein, Dan J, Abe, Yoshinari, Alonso, Pino, Assogna, Francesca, Banaj, Nerisa, Batistuzzo, Marcelo C, Brem, Silvia, Ciullo, Valentina, Feusner, Jamie, Martínez‐Zalacaín, Ignacio, Menchón, José M, Miguel, Euripedes C, Piacentini, John, Piras, Federica, Sakai, Yuki, Wolters, Lidewij, and Yamada, Kei

Subjects
Biological Psychology, Psychology, Brain Disorders, Clinical Research, Serious Mental Illness, Pediatric, Neurosciences, Mental Health, Mental health, Neurological, Cerebral Cortex, Humans, Machine Learning, Multicenter Studies as Topic, Neuroimaging, Obsessive-Compulsive Disorder, cortical thickness, ENIGMA, mega-analysis, meta-analysis, MRI, obsessive-compulsive disorder, surface area, volume, ENIGMA-OCD working group, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Published
2022

10. Correction: The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Author

Bruin, Willem B., Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea L., Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan A. J. P., Echevarria, Marco A. N., Eng, Goi Khia, Ferreira, Sónia, Feusner, Jamie D., Grazioplene, Rachael G., Gruner, Patricia, Guo, Joyce Y., Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo Q., Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun Soo, Lazaro, Luisa, Li, Chiang-Shan R., Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose M., Moreira, Pedro S., Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan C., Nurmi, Erika L., Zorrilla, Jose C. Pariente, Piacentini, John, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan Y. C., Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair H., Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily R., Evelyn Stewart, S., Szeszko, Philip R., Tang, Jinsong, Thomopoulos, Sophia I., Thorsen, Anders L., Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya M., Venkatasubramanian, Ganesan, Vetter, Nora C., Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke A., van Marle, Hein J. F., van de Mortel, Laurens A., van der Straten, Anouk, van der Werf, Ysbrand D., Thompson, Paul M., Stein, Dan J., van den Heuvel, Odile A., and van Wingen, Guido A.

Published
2023
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11. Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters.

Author

Bruin, Willem B, Taylor, Luke, Thomas, Rajat M, Shock, Jonathan P, Zhutovsky, Paul, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Assogna, Francesca, Benedetti, Francesco, Beucke, Jan C, Boedhoe, Premika SW, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Brennan, Brian P, Buitelaar, Jan K, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Dallaspezia, Sara, Denys, Damiaan, Ely, Benjamin A, Feusner, Jamie D, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Gruner, Patricia, Gürsel, Deniz A, Hauser, Tobias U, Hirano, Yoshiyuki, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Ivanov, Iliyan, James, Anthony, Jaspers-Fayer, Fern, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kuno, Masaru, Kvale, Gerd, Kwon, Jun Soo, Liu, Yanni, Lochner, Christine, Lázaro, Luisa, Marques, Paulo, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Moreira, Pedro S, Morer, Astrid, Morgado, Pedro, Nakagawa, Akiko, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, O'Neill, Joseph, Pariente, Jose C, Perriello, Chris, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Rus-Oswald, Oana G, Sakai, Yuki, Sato, João R, Schmaal, Lianne, Shimizu, Eiji, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stern, Emily R, Stevens, Michael C, Stewart, S Evelyn, Szeszko, Philip R, Tolin, David F, Venkatasubramanian, Ganesan, Wang, Zhen, Yun, Je-Yeon, van Rooij, Daan, ENIGMA-OCD Working Group, Thompson, Paul M, van den Heuvel, Odile A, Stein, Dan J, and van Wingen, Guido A

Subjects
ENIGMA-OCD Working Group, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.

Published
2020

13. Mapping Cortical and Subcortical Asymmetry in Obsessive-Compulsive Disorder: Findings From the ENIGMA Consortium

Author

Kong, Xiang-Zhen, Boedhoe, Premika SW, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Arnold, Paul D, Assogna, Francesca, Baker, Justin T, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Brennan, Brian P, Buitelaar, Jan, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Dallaspezia, Sara, Denys, Damiaan, Ely, Benjamin A, Feusner, Jamie, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Glahn, David C, Gruner, Patricia, Gürsel, Deniz A, Hauser, Tobias U, Hirano, Yoshiyuki, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, James, Anthony, Jaspers-Fayer, Fern, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kuno, Masaru, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Liu, Yanni, Lochner, Christine, Marques, Paulo, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Medland, Sarah E, Menchón, José M, Minuzzi, Luciano, Moreira, Pedro S, Morer, Astrid, Morgado, Pedro, Nakagawa, Akiko, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, O'Neill, Joseph, Pariente, Jose C, Perriello, Chris, Piacentini, John, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, YC Janardhan, Rus-Oswald, Oana Georgiana, Sakai, Yuki, Sato, Joao R, Schmaal, Lianne, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stern, Emily R, Stevens, Michael C, Stewart, S Evelyn, Szeszko, Philip R, Tolin, David F, Tsuchiyagaito, Aki, van Rooij, Daan, van Wingen, Guido A, Venkatasubramanian, Ganesan, Wang, Zhen, Yun, Je-Yeon, Group, ENIGMA OCD Working, Anticevic, Alan, Banaj, Nerisa, and Bargalló, Nuria

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Serious Mental Illness, Mental Health, Neurosciences, Brain Disorders, Clinical Research, Anxiety Disorders, Neurological, Mental health, Adult, Brain, Brain Mapping, Child, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Obsessive-Compulsive Disorder, Thalamus, Brain asymmetry, Laterality, Mega-analysis, Obsessive-compulsive disorder, Pallidum, ENIGMA OCD Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundLateralized dysfunction has been suggested in obsessive-compulsive disorder (OCD). However, it is currently unclear whether OCD is characterized by abnormal patterns of brain structural asymmetry. Here we carried out what is by far the largest study of brain structural asymmetry in OCD.MethodsWe studied a collection of 16 pediatric datasets (501 patients with OCD and 439 healthy control subjects), as well as 30 adult datasets (1777 patients and 1654 control subjects) from the OCD Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium. Asymmetries of the volumes of subcortical structures, and of measures of regional cortical thickness and surface areas, were assessed based on T1-weighted magnetic resonance imaging scans, using harmonized image analysis and quality control protocols. We investigated possible alterations of brain asymmetry in patients with OCD. We also explored potential associations of asymmetry with specific aspects of the disorder and medication status.ResultsIn the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward; Cohen's d = 0.19) and the pallidum (less leftward; d = -0.21). Additional analyses suggested putative links between these asymmetry patterns and medication status, OCD severity, or anxiety and depression comorbidities. No significant case-control differences were found in the adult datasets.ConclusionsThe results suggest subtle changes of the average asymmetry of subcortical structures in pediatric OCD, which are not detectable in adults with the disorder. These findings may reflect altered neurodevelopmental processes in OCD.

Published
2020

14. Corrigendum

Author

Yun, Je-Yeon, Boedhoe, Premika SW, Vriend, Chris, Jahanshad, Neda, Abe, Yoshinari, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fouche, Jean-Paul, Gimenez, Monica, Gruner, Patricia, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Ikari, Keisuke, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Lazaro, Luisa, Lochner, Christine, Marques, Paulo, Marsh, Rachel, Martinez-Zalacain, Ignacio, Mataix-Cols, David, Menchon, Jose M, Minuzzi, Luciano, Morgado, Pedro, Moreira, Pedro, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, O'Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, van Wingen, Guido A, Xu, Jian, Xu, Xiufeng, Zhao, Qing, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, and Kwon, Jun Soo

Subjects
Biomedical and Clinical Sciences, Health Sciences, Psychology, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Published
2020

15. Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Author

Yun, Je-Yeon, Boedhoe, Premika SW, Vriend, Chris, Jahanshad, Neda, Abe, Yoshinari, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fouche, Jean-Paul, Giménez, Mònica, Gruner, Patricia, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Ikari, Keisuke, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Lazaro, Luisa, Lochner, Christine, Marques, Paulo, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morgado, Pedro, Moreira, Pedro, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, O’Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, van Wingen, Guido A, Xu, Jian, Xu, Xiufeng, Zhao, Qing, van den Heuvel, Odile3 A, Stein, Dan J, Thompson, Paul M, Ik, Kang, and Cho, K

Subjects
Mental Health, Brain Disorders, Serious Mental Illness, Clinical Research, Neurosciences, Neurological, Mental health, Adult, Brain, Cerebral Cortex, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Obsessive-Compulsive Disorder, brain structural covariance network, graph theory, obsessive-compulsive disorder, pharmacotherapy, illness duration, ENIGMA-OCD working group, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P

Published
2020

16. Sample size requirement for achieving multisite harmonization using structural brain MRI features

Author

Viswanath, Biju, Rao, Naren P., Narayanaswamy, Janardhanan C., Sivakumar, Palanimuthu T., Kandasamy, Arun, Kesavan, Muralidharan, Mehta, Urvakhsh Meherwan, Mukherjee, Odity, Purushottam, Meera, Mehta, Bhupesh, Kandavel, Thennarasu, Binukumar, B., Saini, Jitender, Jayarajan, Deepak, Shyamsundar, A., Moirangthem, Sydney, Vijay Kumar, K.G., Mahadevan, Jayant, Holla, Bharath, Thirthalli, Jagadisha, Gangadhar, Bangalore N., Murthy, Pratima, Panicker, Mitradas M., Bhalla, Upinder S., Chattarji, Sumantra, Benegal, Vivek, Varghese, Mathew, Reddy, Janardhan Y.C., Raghu, Padinjat, Rao, Mahendra, Jain, Sanjeev, Parekh, Pravesh, Vivek Bhalerao, Gaurav, John, John P., and Venkatasubramanian, G.

Published
2022
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17. Neurohemodynamic correlates of BDNF gene expression in schizophrenia patients with working memory deficits: A functional MRI study

Author

Selvaraj, Sowmya, Shivakumar, Venkataram, Kavya, Paranthaman V., Mullapudi, Thrinath, Bhalerao, Gaurav, Sreeraj, Vanteemar S., Suhas, Satish, Dinakaran, Damodharan, Parlikar, Rujuta, Chhabra, Harleen, Narayanaswamy, Janardhanan C., Debnath, Monojit, Rao, Naren P., Muralidharan, Kesavan, and Venkatasubramanian, Ganesan

Published
2022
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18. An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group

Author

Boedhoe, Premika SW, Heymans, Martijn W, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Gruner, Patricia, Hanna, Gregory L, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun Soo, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morer, Astrid, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nishida, Seiji, Nurmi, Erika L, O'Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Reess, Tim J, Sakai, Yuki, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, van Wingen, Guido A, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Yun, Je-Yeon, Working-Group, ENIGMA-OCD, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, and Twisk, Jos WR

Subjects
Biomedical and Clinical Sciences, Information and Computing Sciences, Neurosciences, Applied Computing, Machine Learning, neuroimaging, MRI, IPD meta-analysis, mega-analysis, linear mixed-effect models, ENIGMA-OCD Working-Group, Cognitive Sciences, Applied computing, Machine learning
Abstract

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses. Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods. Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models. Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

Published
2019

20. The thalamus and its subnuclei—a gateway to obsessive-compulsive disorder

Author

Weeland, Cees J., Kasprzak, Selina, de Joode, Niels T., Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H., Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargallo, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Beucke, Jan C., Bollettini, Irene, Brecke, Vilde, Brem, Silvia, Cappi, Carolina, Cheng, Yuqi, Cho, Kang Ik K., Costa, Daniel L. C., Dallaspezia, Sara, Denys, Damiaan, Eng, Goi Khia, Ferreira, Sónia, Feusner, Jamie D., Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael G., Gruner, Patricia, He, Mengxin, Hirano, Yoshiyuki, Hoexter, Marcelo Q., Huyser, Chaim, Hu, Hao, Jaspers-Fayer, Fern, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun Soo, Lazaro, Luisa, Li, Chiang-shan R., Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, Jose M., Minnuzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Nakagawa, Akiko, Nakamae, Takashi, Narayanaswamy, Janardhanan C., Nurmi, Erika L., Ortiz, Ana E., Pariente, Jose C., Piacentini, John, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Y. C. Janardhan, Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Helen Blair, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily R., Stevens, Michael C., Stewart, S. Evelyn, Szeszko, Philip R., Takahashi, Jumpei, Tanamatis, Tais, Tang, Jinsong, Thorsen, Anders Lillevik, Tolin, David, van der Werf, Ysbrand D., van Marle, Hein, van Wingen, Guido A., Vecchio, Daniela, Venkatasubramanian, G., Walitza, Susanne, Wang, Jicai, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij H., Xu, Xiufeng, Yun, Je-Yeon, Zhao, Qing, White, Tonya, Thompson, Paul M., Stein, Dan J., van den Heuvel, Odile A., and Vriend, Chris

Published
2022
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22. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023: Towards Personalized Approaches to Depression Treatment.

Author

Berk, Michael, Agustini, Bruno, Forbes, Malcolm, Jacka, Felice N., Narayanaswamy, Janardhanan C., and Penninx, Brenda W.J.H.

Subjects
PSYCHOTHERAPY, PERSONALITY disorders, SEROTONIN uptake inhibitors, MENTAL depression, DIETARY patterns
Abstract

The Canadian Network for Mood and Anxiety Treatments (CANMAT) has released updated guidelines for the treatment of depression. The guidelines emphasize personalized care for individuals with major depressive disorder, taking into account their unique needs and preferences. The guidelines also highlight the importance of persistence in treatment, as studies have shown that continued treatment can lead to significant benefits. The guidelines recommend considering tricyclic antidepressants, monoamine oxidase inhibitors, and lithium as treatment options, despite their limited use in routine practice. Additionally, lifestyle interventions such as exercise, improved diet, and sleep hygiene are now incorporated into treatment plans. The guidelines also recognize the benefit of combining biological and psychological therapies. Overall, the guidelines aim to provide clinicians with evidence-based recommendations while acknowledging the complexity and heterogeneity of depression. [Extracted from the article]

Published
2024
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23. Cortical Abnormalities Associated With Pediatric and Adult Obsessive-Compulsive Disorder: Findings From the ENIGMA Obsessive-Compulsive Disorder Working Group

Author

Boedhoe, Premika SW, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Gruner, Patricia, Hanna, Gregory L, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun Soo, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morer, Astrid, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nishida, Seiji, Nurmi, Erika, O’Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Reess, Tim J, Sakai, Yuki, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, van Wingen, Guido A, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Yun, Je-Yeon, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, Bargalló, Nuria, Brandeis, Daniel, Buimer, Elizabeth, Busatto, Geraldo F, de Vries, Froukje E, de Wit, Stella J, Drechsler, Renate, and Falini, Andrea

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Pediatric, Neurosciences, Mental Health, Serious Mental Illness, Brain Disorders, Neurological, Mental health, Adolescent, Adult, Age of Onset, Cerebral Cortex, Child, Frontal Lobe, Humans, Magnetic Resonance Imaging, Obsessive-Compulsive Disorder, Parietal Lobe, Reference Values, Temporal Lobe, Young Adult, ENIGMA-OCD Working Group, ENIGMA OCD Working Group, Cortical Thickness, FreeSurfer, MRI, Surface Area, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

ObjectiveBrain imaging studies of structural abnormalities in OCD have yielded inconsistent results, partly because of limited statistical power, clinical heterogeneity, and methodological differences. The authors conducted meta- and mega-analyses comprising the largest study of cortical morphometry in OCD ever undertaken.MethodT1-weighted MRI scans of 1,905 OCD patients and 1,760 healthy controls from 27 sites worldwide were processed locally using FreeSurfer to assess cortical thickness and surface area. Effect sizes for differences between patients and controls, and associations with clinical characteristics, were calculated using linear regression models controlling for age, sex, site, and intracranial volume.ResultsIn adult OCD patients versus controls, we found a significantly lower surface area for the transverse temporal cortex and a thinner inferior parietal cortex. Medicated adult OCD patients also showed thinner cortices throughout the brain. In pediatric OCD patients compared with controls, we found significantly thinner inferior and superior parietal cortices, but none of the regions analyzed showed significant differences in surface area. However, medicated pediatric OCD patients had lower surface area in frontal regions. Cohen's d effect sizes varied from -0.10 to -0.33.ConclusionsThe parietal cortex was consistently implicated in both adults and children with OCD. More widespread cortical thickness abnormalities were found in medicated adult OCD patients, and more pronounced surface area deficits (mainly in frontal regions) were found in medicated pediatric OCD patients. These cortical measures represent distinct morphological features and may be differentially affected during different stages of development and illness, and possibly moderated by disease profile and medication.

Published
2018

24. An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group.

Author

Boedhoe, Premika, Heymans, Martijn, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul, Batistuzzo, Marcelo, Benedetti, Francesco, Beucke, Jan, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Calvo, Rosa, Cheng, Yuqi, Cho, Kang, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie, Fitzgerald, Kate, Fouche, Jean-Paul, Fridgeirsson, Egill, Gruner, Patricia, Hanna, Gregory, Hibar, Derrek, Hoexter, Marcelo, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José, Minuzzi, Luciano, Morer, Astrid, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan, Nishida, Seiji, Nurmi, Erika, Oneill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, Y, Reess, Tim, Sakai, Yuki, Sato, Joao, Simpson, H, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael, Szeszko, Philip, Tolin, David, van Wingen, Guido, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Yun, Je-Yeon, Thompson, Paul, Stein, Dan, van den Heuvel, Odile, and Twisk, Jos

Subjects
IPD meta-analysis, MRI, linear mixed-effect models, mega-analysis, neuroimaging
Abstract

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses. Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods. Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models. Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

Published
2018

34. Leukocyte mitochondrial DNA copy number in schizophrenia

Author

Shivakumar, Venkataram, Rajasekaran, Ashwini, Subbanna, Manjula, Kalmady, Sunil Vasu, Venugopal, Deepthi, Agrawal, Rimjhim, Amaresha, Anekal C., Agarwal, Sri Mahavir, Joseph, Boban, Narayanaswamy, Janardhanan C., Debnath, Monojit, Venkatasubramanian, Ganesan, and Gangadhar, Bangalore N.

Published
2020
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37. Tolerance of transcranial direct current stimulation in psychiatric disorders: An analysis of 2000+ sessions

Author

Chhabra, Harleen, Bose, Anushree, Shivakumar, Venkataram, Agarwal, Sri Mahavir, Sreeraj, Vanteemar S., Shenoy, Sonia, Hazari, Nandita, Dinakaran, Damodharan, Parlikar, Rujuta, Koparde, Vinayak, Ramesh, Vinutha, Biswal, Jitendriya, Murugaraja, Venkatachalam, Gowda, Shayanth Manche, Chand, Prabhat K., Sivakumar, Palanimuthu T., Kalmady, Sunil V, Narayanaswamy, Janardhanan C., Murthy, Pratima, Girimaji, Satish C., and Venkatasubramanian, Ganesan

Published
2020
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38. Long-term Impact of the COVID-19 Pandemic on Obsessive-Compulsive Disorder

Author

Sharma, Lavanya P, primary, Balachander, Srinivas, additional, Thatikonda, Navya Spurthi, additional, Ganesh, Uma Maheswari, additional, Kishore, Chethana, additional, Bhattacharya, Mahashweta, additional, Thamby, Abel, additional, TS, Jaisoorya, additional, Narayanaswamy, Janardhanan C, additional, Arumugham, Shyam Sundar, additional, and Reddy, YC Janardhan, additional

Published
2023
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