Zobrazeno 1 - 10
of 103
pro vyhledávání: '"ABBAS, Kausar"'
Autor:
Abbas, Kausar, Liu, Mintao, Wang, Michael, Duong-Tran, Duy, Tipnis, Uttara, Amico, Enrico, Kaplan, Alan D., Dzemidzic, Mario, Kareken, David, Ances, Beau M., Harezlak, Jaroslaw, Goñi, Joaquín
Functional connectomes (FCs) contain pairwise estimations of functional couplings based on pairs of brain regions activity. FCs are commonly represented as correlation matrices that are symmetric positive definite (SPD) lying on or inside the SPD man
Externí odkaz:
http://arxiv.org/abs/2212.06394
Autor:
Chiêm, Benjamin, Abbas, Kausar, Amico, Enrico, Duong-Tran, Duy Anh, Crevecoeur, Frédéric, Goñi, Joaquín
Functional connectivity quantifies the statistical dependencies between the activity of brain regions, measured using neuroimaging data such as functional MRI BOLD time series. The network representation of functional connectivity, called a Functiona
Externí odkaz:
http://arxiv.org/abs/2011.10079
Autor:
Tipnis, Uttara, Abbas, Kausar, Tran, Elizabeth, Amico, Enrico, Shen, Li, Kaplan, Alan D., Goñi, Joaquín
The assessment of brain fingerprints has emerged in the recent years as an important tool to study individual differences and to infer quality of neuroimaging datasets. Studies so far have mainly focused on connectivity fingerprints between different
Externí odkaz:
http://arxiv.org/abs/2011.05212
Autor:
Abbas, Kausar, Liu, Mintao, Venkatesh, Manasij, Amico, Enrico, Kaplan, Alan David, Ventresca, Mario, Pessoa, Luiz, Harezlak, Jaroslaw, Goñi, Joaquín
Publikováno v:
Brain Connectivity, 2021
Background: Functional connectomes (FCs), have been shown to provide a reproducible individual fingerprint, which has opened the possibility of personalized medicine for neuro/psychiatric disorders. Thus, developing accurate ways to compare FCs is es
Externí odkaz:
http://arxiv.org/abs/2003.05393
Autor:
Abbas, Kausar, Amico, Enrico, Svaldi, Diana Otero, Tipnis, Uttara, Duong-Tran, Duy Anh, Liu, Mintao, Rajapandian, Meenusree, Harezlak, Jaroslaw, Ances, Beau M., Goñi, Joaquín
It has been well established that Functional Connectomes (FCs), as estimated from functional MRI (fMRI) data, have an individual fingerprint that can be used to identify an individual from a population (subject-identification). Although identificatio
Externí odkaz:
http://arxiv.org/abs/2001.06605
Autor:
Abbas, Kausar, Liu, Mintao, Wang, Michael, Duong-Tran, Duy, Tipnis, Uttara, Amico, Enrico, Kaplan, Alan D., Dzemidzic, Mario, Kareken, David, Ances, Beau M., Harezlak, Jaroslaw, Goñi, Joaquín
Publikováno v:
In iScience 15 September 2023 26(9)
The Identifiability Framework (If) has been shown to improve differential identifiability (reliability across-sessions and -sites, and differentiability across-subjects) of functional connectomes for a variety of fMRI tasks. But having a robust singl
Externí odkaz:
http://arxiv.org/abs/1911.10193
Autor:
Amico, Enrico, Abbas, Kausar, Duong-Tran, Duy Anh, Tipnis, Uttara, Rajapandian, Meenusree, Chumin, Evgeny, Ventresca, Mario, Harezlak, Jaroslaw, Goñi, Joaquín
Modeling communication dynamics in the brain is a key challenge in network neuroscience. We present here a framework that combines two measurements for any system where different communication processes are taking place on top of a fixed structural t
Externí odkaz:
http://arxiv.org/abs/1911.02601
Autor:
Svaldi, Diana O., Goñi, Joaquín, Abbas, Kausar, Amico, Enrico, Clark, David G., Muralidharan, Charanya, Dzemidzic, Mario, West, John D., Risacher, Shannon L., Saykin, Andrew J., Apostolova, Liana G.
Functional connectivity, as estimated using resting state fMRI, has shown potential in bridging the gap between pathophysiology and cognition. However, clinical use of functional connectivity biomarkers is impeded by unreliable estimates of individua
Externí odkaz:
http://arxiv.org/abs/1908.06197
Autor:
Sadiq, Muhammad Usman, Svaldi, Diana, Shenk, Trey, Breedlove, Evan, Poole, Victoria, Tamer, Greg, Abbas, Kausar, Talavage, Thomas
Publikováno v:
Originally published at: Annual meeting of the Organization for Human Brain Mapping, OHBM 2018
Several studies have used structural correlation networks, derived from anatomical covariance of brain regions, to analyze neurologic changes associated with multiple sclerosis, schizophrenia and breast cancer [1][2]. Graph-theoretical analyses of hu
Externí odkaz:
http://arxiv.org/abs/1904.10924