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D Calhoun

Showing results (381-390 of 1,451) with videos related to

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Neuroimage. Clinical|July 24, 2018
Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learningVictor M Vergara, Andrew R Mayer, Kent A Kiehl, et al.
Imaging Neuroscience (Cambridge, Mass.)|June 22, 2026
Multimodal subspace independent vector analysis effectively captures latent relationships between brain structure and functionXinhui Li, Peter Kochunov, Tulay Adali, et al.
IEEE Transactions on Signal Processing : a Publication of the IEEE Signal Processing Society|July 17, 2010
On entropy rate for the complex domainWei Xiong, Tülay Adalı, Yi-Ou Li, et al.
Neuroimage|March 15, 2011
Dynamic modeling of neuronal responses in fMRI using cubature Kalman filteringMartin Havlicek, Karl J Friston, Jiri Jan, et al.
Schizophrenia Research|October 8, 2013
State-related functional integration and functional segregation brain networks in schizophreniaQingbao Yu, Jing Sui, Kent A Kiehl, et al.
IEEE Transactions on Bio-Medical Engineering|August 20, 2016
A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information FlowRobyn L Miller, Victor Manuel Vergara, David B Keator, et al.
Neuroimage|July 5, 2011
Characterization of groups using composite kernels and multi-source fMRI analysis data: application to schizophreniaEduardo Castro, Manel Martínez-Ramón, Godfrey Pearlson, et al.
Frontiers in Human Neuroscience|March 1, 2012
A selective review of multimodal fusion methods in schizophreniaJing Sui, Qingbao Yu, Hao He, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 9, 2015
Brain functional networks extraction based on fMRI artifact removal: Single subject and group approachesYuhui Du, Elena A Allen, Hao He, et al.
Human Brain Mapping|September 29, 2021
A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRIBruno Hebling Vieira, Julien Dubois, Vince D Calhoun, et al.
Pageof 146

Showing results (381-390 of 1,451) with videos related to

Sort By:
Pageof 146
Neuroimage. Clinical|July 24, 2018
Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learningVictor M Vergara, Andrew R Mayer, Kent A Kiehl, et al.
Imaging Neuroscience (Cambridge, Mass.)|June 22, 2026
Multimodal subspace independent vector analysis effectively captures latent relationships between brain structure and functionXinhui Li, Peter Kochunov, Tulay Adali, et al.
IEEE Transactions on Signal Processing : a Publication of the IEEE Signal Processing Society|July 17, 2010
On entropy rate for the complex domainWei Xiong, Tülay Adalı, Yi-Ou Li, et al.
Neuroimage|March 15, 2011
Dynamic modeling of neuronal responses in fMRI using cubature Kalman filteringMartin Havlicek, Karl J Friston, Jiri Jan, et al.
Schizophrenia Research|October 8, 2013
State-related functional integration and functional segregation brain networks in schizophreniaQingbao Yu, Jing Sui, Kent A Kiehl, et al.
IEEE Transactions on Bio-Medical Engineering|August 20, 2016
A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information FlowRobyn L Miller, Victor Manuel Vergara, David B Keator, et al.
Neuroimage|July 5, 2011
Characterization of groups using composite kernels and multi-source fMRI analysis data: application to schizophreniaEduardo Castro, Manel Martínez-Ramón, Godfrey Pearlson, et al.
Frontiers in Human Neuroscience|March 1, 2012
A selective review of multimodal fusion methods in schizophreniaJing Sui, Qingbao Yu, Hao He, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 9, 2015
Brain functional networks extraction based on fMRI artifact removal: Single subject and group approachesYuhui Du, Elena A Allen, Hao He, et al.
Human Brain Mapping|September 29, 2021
A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRIBruno Hebling Vieira, Julien Dubois, Vince D Calhoun, et al.
Pageof 146