Deciphering the Laminar-Specific Functional Connectivity and its Vascular and Neural Correlates
In this proposal, a merged effort from three research groups is made to study the neural and vascular correlates of laminar-specific resting state fMRI signal fluctuation, which underlies the functional connectivity mapping in both human and animal models at varied brain states. Since the first report of large scale spatial signal correlation in fMRI images (Biswal et al, 1995), the drastically improved spatiotemporal resolution of high-field fMRI has revealed a number of key networks in the brain relevant to the default mode, attention, cognition, and sensorimotor connections. However, the millimeter size of voxels for resting-state and task fMRI results in fMRI signal dominated by large venous vessels. Although numerous studies have been designed to exclude signal contribution from veins, the neuronal correlates of resting-state and task fMRI signal has been heavily linked to vascular contributions. It remains a challenge to disentangle the distinct neuronal and vascular contribution to fMRI signal fluctuation given the limited spatial and temporal resolution. In this proposal, we will acquire a so far unique and high spatiotemporal laminar specific fMRI data using a line-scanning scheme-based fast low angle shot (FLASH) and balanced steady-state free precession (bSSFP) methods in the rat brain during rest and stimulation. This proposal aims to characterize the laminar-specific spatiotemporal correlation features of fMRI signal fluctuations, and to decipher the vascular and neural correlates to large-scale connectivity patterns of the long-range network, which has been reported to be crucial for specific cognitive brain states.
Dr. Xin Yu, Translational NeuroImaging and Neural Control Group, High Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
Prof. Klaus Scheffler, High Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
Bharat Biswal, Ph.D. Professor, Department of Biomedical Engineering, New Jersey Institute of Technology University Heights
Funding total: 460.000€