Year of Publication: 2024
Project: Layer Specific fMRI
FIM Authors:
Authors:
  • Yuhui Chai
  • Tyler Morgan
  • Hua Xie
  • Linqing Li
  • Laurentius Huber
  • Peter Bandettini
  • Bradley P. Sutton
Abstract:

Neuroscientific investigations at the cortical layer level not only enrich our knowledge of cortical micro-circuitry in vivo, but also help bridge the gap between macroscopic (e.g., conventional fMRI, behavior) and microscopic (e.g., extracellular recordings) measures of brain function. While laminar fMRI studies have extensively explored the evoked cortical response in multiple subsystems, the investigation of the laminar component of functional networks throughout the entire brain has been hindered due to constraints in high-resolution layer-fMRI imaging methodologies. Our study addresses this gap by introducing an innovative layer-specific 3D VAPER (integrated VASO and Perfusion contrast) technique in humans at 7 T, for achieving fMRI at high resolution (800 µm isotropic), high specificity (not biased toward unspecific vein signals as BOLD), high sensitivity (robust measurement at submillimeter resolution), high spatial accuracy (analysis in native fMRI space), near-whole-brain coverage (cerebellum not included), and eventually extending layer fMRI to more flexible connectivity-based experiment designs. To demonstrate its effectiveness, we collected 0.8-mm isotropic fMRI data during both resting-state and movie-watching scenarios, established a layer-specific functional connectivity analysis pipeline from individual to group levels, and explored the role of different cortical layers in maintaining functional networks. Our results revealed distinct layer-specific connectivity patterns within the default mode, somatomotor, and visual networks, as well as at the global hubness level. The cutting-edge technique and insights derived from our exploration into near-whole-brain layer-specific connectivity provide unparalleled understanding of the organization principles and underlying mechanisms governing communication between different brain regions.


Data
Code
Journal: Imaging Neuroscience
Volume: 2
URL: https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00140/120467
DOI: https://doi.org/10.1162/imag_a_00140