2022
DOI: 10.1101/2022.08.19.504502
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Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset

Abstract: Cortical depth-dependent functional magnetic resonance image (fMRI), also known as layer-fMRI, has the potential to capture directional neural information flow of brain computations within and across large-scale cortical brain networks. E.g., layer-fMRI can differentiate feedforward and feedback cortical input in hierarchically organized brain networks. Recent advancements in 3D-EPI sampling approaches and MR contrast generation strategies have allowed proof-of-principle studies showing that layer-fMRI can pro… Show more

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Cited by 5 publications
(3 citation statements)
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“…2022 ). For instance, conjoining the development of new VASO acquisition protocols ( Koiso et al. 2022 , Dresbach et al.…”
Section: Discussionmentioning
confidence: 99%
“…2022 ). For instance, conjoining the development of new VASO acquisition protocols ( Koiso et al. 2022 , Dresbach et al.…”
Section: Discussionmentioning
confidence: 99%
“…However, if the goal is to study brain-wide distributed networks, this is not sufficient. Therefore, sacrificing imaging speed might be necessary to investigate connectivity between distant brain regions across cortical depth (Koiso et al, 2022).…”
Section: Discussionmentioning
confidence: 99%
“…In recent years, this method (specifically slice-selective slab-inversion [SS-SI] VASO [Huber et al, 2014], henceforth referred to as VASO) has gained popularity for investigations of cortical depth-dependent signal changes at ultra-high fields ( > 7T) due to its high specificity to the microvasculature and hence the underlying neural activity (e.g. Faes et al, 2023; Haenelt et al, 2023; Huber et al, 2017; Koiso et al, 2023; Persichetti et al, 2020; Pizzuti et al, 2023; Yu et al, 2019; for other VASO variants at ultra-high field, see e.g. Chai et al, 2020; Hua et al, 2013).…”
Section: Introductionmentioning
confidence: 99%