Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Brian eCaffo"'
Publikováno v:
Frontiers in Neuroscience, Vol 10 (2016)
Independent Component analysis (ICA) is a widely used technique for separating signals that have been mixed together. In this manuscript, we propose a novel ICA algorithm using density estimation and maximum likelihood, where the densities of the sig
Externí odkaz:
https://doaj.org/article/208004ae9f7446dcb95c3df564478e19
Publikováno v:
Frontiers in Neuroscience, Vol 9 (2015)
Methodology for linking fMRI BOLD signal distributional changes associated with paradigm-related learning remains needed. Herein we consider settings where task related activation may be present before and after learning, yet the distribution of acti
Externí odkaz:
https://doaj.org/article/ce827bd6daa64966aaf890842af1b5fe
Autor:
Ani eEloyan, John eMuschelli, Mary Beth eNebel, Han eLiu, Fang eHan, Tuo eZhao, Anita D Barber, Suresh eJoel, James J. Pekar, Stewart H Mostofsky, Brian eCaffo
Publikováno v:
Frontiers in Systems Neuroscience, Vol 6 (2012)
Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictabilit
Externí odkaz:
https://doaj.org/article/05356859218243f4b69ddf0cb882d737
Autor:
Ani eEloyan, John eMuschelli, Mary Beth eNebel, Han eLiu, Fang eHan, Tuo eZhao, Anita D Barber, Suresh eJoel, James J. Pekar, Stewart H Mostofsky, Brian eCaffo
Publikováno v:
Scopus-Elsevier
Frontiers in Systems Neuroscience
Frontiers in Systems Neuroscience, Vol 6 (2012)
Frontiers in Systems Neuroscience
Frontiers in Systems Neuroscience, Vol 6 (2012)
Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictabilit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7f774b4ac4f195fb2f079f6495c274b
http://www.scopus.com/inward/record.url?eid=2-s2.0-84866012927&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84866012927&partnerID=MN8TOARS
