Bayesian longitudinal tensor response regression for modeling neuroplasticity

Autor: Kundu, Suprateek, Reinhardt, Alec, Song, Serena, Han, Joo, Meadows, M. Lawson, Crosson, Bruce, Krishnamurthy, Venkatagiri

A major interest in longitudinal neuroimaging studies involves investigating voxel-level neuroplasticity due to treatment and other factors across visits. However, traditional voxel-wise methods are beset with several pitfalls, which can compromise t

Externí odkaz: http://arxiv.org/abs/2309.10065

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Bayesian longitudinal tensor response regression for modeling neuroplasticity.

Autor: Kundu S; Department of Biostatistics, UT MD Anderson Cancer Center, Houston, Texas, USA., Reinhardt A; Department of Biostatistics, UT MD Anderson Cancer Center, Houston, Texas, USA., Song S; Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center, Decatur, Georgia, USA., Han J; Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center, Decatur, Georgia, USA., Meadows ML; Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center, Decatur, Georgia, USA., Crosson B; Department of Neurology, Emory University, Atlanta, Georgia, USA.; Department of Imaging and Radiological Sciences, Emory University, Atlanta, Georgia, USA., Krishnamurthy V; Division of Geriatrics and Gerontology, Emory University, Atlanta, Georgia, USA.

Publikováno v: Human brain mapping [Hum Brain Mapp] 2023 Dec 15; Vol. 44 (18), pp. 6326-6348. Date of Electronic Publication: 2023 Nov 01.