Cerebral blood volume (CBV) and cerebral blood flow (CBF)-based functional magnetic resonance imaging (fMRI) have proven to be more laminar-specific than blood-oxygen-level-dependent (BOLD) contrast fMRI, but they suffer from relatively low sensitivity. In previous work, we integrated CBV and CBF into one contrast using DANTE (Delay Alternating with Nutation for Tailored Excitation) pulse trains combined with 3D echo-planar imaging (EPI) to create an integrated blood volume and perfusion (VAPER)-weighted contrast (Chai et al., 2020). Building on this, we have now introduced a magnetization transfer approach to induce a tissue-suppression-based VASO (vascular space occupancy) effect and incorporated it with the VAPER technique to boost the overall sensitivity while maintaining superior laminar specificity, all without altering the original VAPER sequence timing scheme. This magnetization transfer (MT)–VAPER fMRI acquisition alternates between DANTE blood-nulling and MT-tissue-suppression conditions, generating an integrated VASO and perfusion contrast enhanced by MT. Both theoretical and experimental evaluation demonstrated an approximately 30% enhancement in VAPER sensitivity with MT application. This novel MT–VAPER method was empirically validated in human primary motor and visual cortices, demonstrating its superior laminar specificity and robust reproducibility, establishing it as valuable non-BOLD tool for laminar fMRI in human brain function research.

Functional MRI (fMRI) time series are inherently susceptible to the influence of respiratory variations. While many studies treat respiration as a source of noise in fMRI, this study employs natural respiratory variations during high resolution (0.8 mm) fMRI at 7T to formulate a respiration effect related map and then use this map to reduce macrovascular bias for a more laminar-specific fMRI measurement. Our results indicate that respiratory-related signal changes are modulated by breath phase (breathing in/out or in the transition between breath in and out) during fMRI acquisition, with distinct patterns across various brain regions. We demonstrate that respiration maps generated from normal fMRI runs, such as task-oriented sessions, closely resemble those from deep-breath and breath-hold experiments. These maps show a significant correlation with the macro-vasculature automatically segmented based on susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) images. Most crucially, by removing voxels most responsive to respiratory variations, we can refine high-resolution fMRI measurements to be more layer-specific, improving the accuracy of laminar fMRI analysis.

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.