Zobrazeno 1 - 10
of 3 411
pro vyhledávání: '"Stewart, H. A."'
Source detection is a vital part of any astronomical survey analysis pipeline. In addition, a versatile source finder that can recover and handle sources of all morphological types is becoming more important as surveys get bigger and achieve a higher
Externí odkaz:
http://arxiv.org/abs/2410.22508
Publikováno v:
In Journal of Psychiatric Research December 2024 180:103-112
Publikováno v:
In Advances in Kidney Disease and Health November 2024 31(6):523-528
Independent component analysis (ICA) is an unsupervised learning method popular in functional magnetic resonance imaging (fMRI). Group ICA has been used to search for biomarkers in neurological disorders including autism spectrum disorder and dementi
Externí odkaz:
http://arxiv.org/abs/2101.04809
Autor:
Zachary J. Williams, Roseann Schaaf, Karla K. Ausderau, Grace T. Baranek, D. Jonah Barrett, Carissa J. Cascio, Rachel L. Dumont, Ekomobong E. Eyoh, Michelle D. Failla, Jacob I. Feldman, Jennifer H. Foss-Feig, Heather L. Green, Shulamite A. Green, Jason L. He, Elizabeth A. Kaplan-Kahn, Bahar Keçeli-Kaysılı, Keren MacLennan, Zoe Mailloux, Elysa J. Marco, Lisa E. Mash, Elizabeth P. McKernan, Sophie Molholm, Stewart H. Mostofsky, Nicolaas A. J. Puts, Caroline E. Robertson, Natalie Russo, Nicole Shea, John Sideris, James S. Sutcliffe, Teresa Tavassoli, Mark T. Wallace, Ericka L. Wodka, Tiffany G. Woynaroski
Publikováno v:
Molecular Autism, Vol 14, Iss 1, Pp 1-28 (2023)
Abstract Background Differences in responding to sensory stimuli, including sensory hyperreactivity (HYPER), hyporeactivity (HYPO), and sensory seeking (SEEK) have been observed in autistic individuals across sensory modalities, but few studies have
Externí odkaz:
https://doaj.org/article/dea0fb5adbdd44caa46eddfb2fb73bfc
Autor:
D'Souza, Niharika Shimona, Nebel, Mary Beth, Crocetti, Deana, Wymbs, Nicholas, Robinson, Joshua, Mostofsky, Stewart H., Venkataraman, Archana
We propose a novel integrated framework that jointly models complementary information from resting-state functional MRI (rs-fMRI) connectivity and diffusion tensor imaging (DTI) tractography to extract biomarkers of brain connectivity predictive of b
Externí odkaz:
http://arxiv.org/abs/2008.12410
Autor:
D'Souza, Niharika Shimona, Nebel, Mary Beth, Wymbs, Nicholas, Mostofsky, Stewart H., Venkataraman, Archana
We propose a novel optimization framework to predict clinical severity from resting state fMRI (rs-fMRI) data. Our model consists of two coupled terms. The first term decomposes the correlation matrices into a sparse set of representative subnetworks
Externí odkaz:
http://arxiv.org/abs/2009.03238
Autor:
Schirmer, Markus D., Venkataraman, Archana, Rekik, Islem, Kim, Minjeong, Mostofsky, Stewart H., Nebel, Mary Beth, Rosch, Keri, Seymour, Karen, Crocetti, Deana, Irzan, Hassna, Hütel, Michael, Ourselin, Sebastien, Marlow, Neil, Melbourne, Andrew, Levchenko, Egor, Zhou, Shuo, Kunda, Mwiza, Lu, Haiping, Dvornek, Nicha C., Zhuang, Juntang, Pinto, Gideon, Samal, Sandip, Zhang, Jennings, Bernal-Rusiel, Jorge L., Pienaar, Rudolph, Chung, Ai Wern
Large, open-source consortium datasets have spurred the development of new and increasingly powerful machine learning approaches in brain connectomics. However, one key question remains: are we capturing biologically relevant and generalizable inform
Externí odkaz:
http://arxiv.org/abs/2006.03611
Autor:
Horowitz-Kraus, Tzipi, Rosch, Keri, Fotang, Jenny, Mostofsky, Stewart H., Schlaggar, Bradley L., Pekar, James, Taran, Nikolay, Farah, Rola
Publikováno v:
In Cortex November 2023 168:62-75
Autor:
Rosch, Keri S., Batschelett, Mitchell A., Crocetti, Deana, Mostofsky, Stewart H., Seymour, Karen E.
Publikováno v:
In Behavioural Brain Research 24 August 2023 452