Two-dimensional mathematical structure of the human visuotopic map complex in V1, V2, and V3 measured via fMRI at 3 and 7 Tesla

X-nuclear MRS and MRI on a standard clinical proton-only MRI scanner

In light of the growing interest in-vivo deuterium metabolic imaging, hyperpolarized 13C, 15N, 3He, and 129Xe imaging, as well as 31P spectroscopy and imaging in large animals on clinical MR scanners, we demonstrate the use of a (radio)frequency converter system to allow X-nuclear MR spectroscopy (MRS) and MR imaging (MRI) on standard clinical MRI scanners without multinuclear capability. This is not only an economical alternative to the multinuclear system (MNS) provided by the scanner vendors, but also overcomes the frequency bandwidth problem of some vendor-provided MNSs that prohibit users from applications with X-nuclei of low magnetogyric ratio, such as deuterium (6.536 MHz/Tesla) and 15N (-4.316 MHz/Tesla). Here we illustrate the design of the frequency converter system and demonstrate its feasibility for 31P (17.235 MHz/Tesla), 13C (10.708 MHz/Tesla), and 15N MRS and MRI on a clinical MRI scanner without vendor-provided multinuclear hardware.

Extremely fast pRF mapping for real-time applications

Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed cortical activation patterns. This has been suggested to pave the road towards pRF-based brain-computer interface (BCI) communication systems, which would be able to directly decode internally visualized letters from topographically organized brain activity. A major stumbling block for such an application is, however, that the pRF mapping procedure is computationally heavy and time consuming. To address this, we propose a novel and fast pRF mapping procedure that is suitable for real-time applications. The method is built upon hashed-Gaussian encoding of the stimulus, which tremendously reduces computational resources. After the stimulus is encoded, mapping can be performed using either ridge regression for fast offline analyses or gradient descent for real-time applications. We validate our model-agnostic approach in silico, as well as on empirical fMRI data obtained from 3T and 7T MRI scanners. Our approach is capable of estimating receptive fields and their parameters for millions of voxels in mere seconds. This method thus facilitates real-time applications of population receptive field mapping.

Exact geodesics and shortest paths on polyhedral surfaces

We present two algorithms for computing distances along convex and non-convex polyhedral surfaces. The first algorithm computes exact minimal-geodesic distances and the second algorithm combines these distances to compute exact shortest-path distances along the surface. Both algorithms have been extended to compute the exact minimal-geodesic paths and shortest paths. These algorithms have been implemented and validated on surfaces for which the correct solutions are known, in order to verify the accuracy and to measure the run-time performance, which is cubic or less for each algorithm. The exact-distance computations carried out by these algorithms are feasible for large-scale surfaces containing tens of thousands of vertices, and are a necessary component of near-isometric surface flattening methods that accurately transform curved manifolds into flat representations.