Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

Autor: Xi Zhu, Yoojean Kim, Orren Ravid, Xiaofu He, Benjamin Suarez-Jimenez, Sigal Zilcha-Mano, Amit Lazarov, Seonjoo Lee, Chadi G. Abdallah, Michael Angstadt, Christopher L. Averill, C. Lexi Baird, Lee A. Baugh, Jennifer U. Blackford, Jessica Bomyea, Steven E. Bruce, Richard A. Bryant, Zhihong Cao, Kyle Choi, Josh Cisler, Andrew S. Cotton, Judith K. Daniels, Nicholas D. Davenport, Richard J. Davidson, Michael D. DeBellis, Emily L. Dennis, Maria Densmore, Terri deRoon-Cassini, Seth G. Disner, Wissam El Hage, Amit Etkin, Negar Fani, Kelene A. Fercho, Jacklynn Fitzgerald, Gina L. Forster, Jessie L. Frijling, Elbert Geuze, Atilla Gonenc, Evan M. Gordon, Staci Gruber, Daniel W Grupe, Jeffrey P. Guenette, Courtney C. Haswell, Ryan J. Herringa, Julia Herzog, David Bernd Hofmann, Bobak Hosseini, Anna R. Hudson, Ashley A. Huggins, Jonathan C. Ipser, Neda Jahanshad, Meilin Jia-Richards, Tanja Jovanovic, Milissa L. Kaufman, Mitzy Kennis, Anthony King, Philipp Kinzel, Saskia B.J. Koch, Inga K. Koerte, Sheri M. Koopowitz, Mayuresh S. Korgaonkar, John H. Krystal, Ruth Lanius, Christine L. Larson, Lauren A.M. Lebois, Gen Li, Israel Liberzon, Guang Ming Lu, Yifeng Luo, Vincent A. Magnotta, Antje Manthey, Adi Maron-Katz, Geoffery May, Katie McLaughlin, Sven C. Mueller, Laura Nawijn, Steven M. Nelson, Richard W.J. Neufeld, Jack B Nitschke, Erin M. O'Leary, Bunmi O. Olatunji, Miranda Olff, Matthew Peverill, K. Luan Phan, Rongfeng Qi, Yann Quidé, Ivan Rektor, Kerry Ressler, Pavel Riha, Marisa Ross, Isabelle M. Rosso, Lauren E. Salminen, Kelly Sambrook, Christian Schmahl, Martha E. Shenton, Margaret Sheridan, Chiahao Shih, Maurizio Sicorello, Anika Sierk, Alan N. Simmons, Raluca M. Simons, Jeffrey S. Simons, Scott R. Sponheim, Murray B. Stein, Dan J. Stein, Jennifer S. Stevens, Thomas Straube, Delin Sun, Jean Théberge, Paul M. Thompson, Sophia I. Thomopoulos, Nic J.A. van der Wee, Steven J.A. van der Werff, Theo G.M. van Erp, Sanne J.H. van Rooij, Mirjam van Zuiden, Tim Varkevisser, Dick J. Veltman, Robert R.J.M. Vermeiren, Henrik Walter, Li Wang, Xin Wang, Carissa Weis, Sherry Winternitz, Hong Xie, Ye Zhu, Melanie Wall, Yuval Neria, Rajendra A. Morey

Publikováno v: NeuroImage, Vol 283, Iss , Pp 120412- (2023)

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodolo

Externí odkaz: https://doaj.org/article/064745d8320544298a997782e36ec231

Brain hubs defined in the group do not overlap with regions of high inter-individual variability

Autor: Derek M. Smith, Brian T. Kraus, Ally Dworetsky, Evan M. Gordon, Caterina Gratton

Publikováno v: NeuroImage, Vol 277, Iss , Pp 120195- (2023)

Connector ‘hubs’ are brain regions with links to multiple networks. These regions are hypothesized to play a critical role in brain function. While hubs are often identified based on group-average functional magnetic resonance imaging (fMRI) data

Externí odkaz: https://doaj.org/article/0fecb4dcb54f4494aae1cbf07f068def

Using synthetic MR images for distortion correction

Autor: David F. Montez, Andrew N. Van, Ryland L. Miller, Nicole A. Seider, Scott Marek, Annie Zheng, Dillan J. Newbold, Kristen Scheidter, Eric Feczko, Anders J. Perrone, Oscar Miranda-Dominguez, Eric A. Earl, Benjamin P. Kay, Abhinav K. Jha, Aristeidis Sotiras, Timothy O. Laumann, Deanna J. Greene, Evan M. Gordon, M. Dylan Tisdall, Andre van der Kouwe, Damien A. Fair, Nico U.F. Dosenbach

Publikováno v: Developmental Cognitive Neuroscience, Vol 60, Iss , Pp 101234- (2023)

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignmen

Externí odkaz: https://doaj.org/article/624b2578d5a348c7b0f3495968a4e48d

Whole-Brain Resting-State Functional Connectivity Patterns Associated With Pediatric Anxiety and Involuntary Attention Capture

Autor: Michael T. Perino, Michael J. Myers, Muriah D. Wheelock, Qiongru Yu, Jennifer C. Harper, Megan F. Manhart, Evan M. Gordon, Adam T. Eggebrecht, Daniel S. Pine, Deanna M. Barch, Joan L. Luby, Chad M. Sylvester

Publikováno v: Biological Psychiatry Global Open Science, Vol 1, Iss 3, Pp 229-238 (2021)

Background: Pediatric anxiety disorders are linked to dysfunction in multiple functional brain networks, as well as to alterations in the allocation of spatial attention. We used network-level analyses to characterize resting-state functional connect

Externí odkaz: https://doaj.org/article/fc9fe1ac418a401f87499af7669482fa

Functional Connectivity Fingerprints at Rest Are Similar across Youths and Adults and Vary with Genetic Similarity

Autor: Damion V. Demeter, Laura E. Engelhardt, Remington Mallett, Evan M. Gordon, Tehila Nugiel, K. Paige Harden, Elliot M. Tucker-Drob, Jarrod A. Lewis-Peacock, Jessica A. Church

Publikováno v: iScience, Vol 23, Iss 1, Pp - (2020)

Summary: Distinguishing individuals from brain connectivity, and studying the genetic influences on that identification across different ages, improves our basic understanding of functional brain network organization. We applied support vector machin

Externí odkaz: https://doaj.org/article/2478cdd2223149c4bd361481e2d92190