Dynamic brain signals provide key information that can be deciphered for a better understanding of brain function. Functional Magnetic Resonance Imaging (fMRI) has been developed to map not only the activity pattern but also functional connectivity in the whole brain. Although it has been over twenty years since the development of fMRI and the resting-state fMRI, the key challenge of fMRI-based signal interpretation remains to be the temporal and spatial resolution limit of the hemodynamic signal detected by fMRI. In most fMRI studies, the size of these voxels pre-determines the limits of the basic biological conclusion. With recent advancement leading to dramatic improvement in spatiotemporal resolution of MRI, the dynamic signal feature can be better clarified, which will significantly improve our understanding of brain function. 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 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. As connectivity measures are increasingly being used, a number of groups are beginning to focus on mind body interactions. In particular, connectivity measures, both local and global are being used in brain regions including insula and thalamus to better understand more complex brain behavior interactions.
This proposal has the potential for a tremendous impact on science and society in general. The novel brain connectivity data will yield detailed insight into brain networks, based on specific neural correlate features in the brain. This is of fundamental interests for neurophysiological and computational neuroscientists and would provide insights into mind body interactions by helping to focus on specific brain regions including insula and thalamus.
|Pais-Roldán, Patricia; Biswal, Bharat; Scheffler, Klaus et al. (2018) Identifying Respiration-Related Aliasing Artifacts in the Rodent Resting-State fMRI. Front Neurosci 12:788|