Diagnostic performance and accuracy of 3-D spoiled gradient-dual-echo MRI with water- and fat-signal separation in liver-fat quantification: comparison to liver biopsy

To prospectively evaluate a 3-dimensional spoiled gradient-dual-echo (3D SPGR-DE) magnetic resonance imaging (MRI) sequence for the qualitative and quantitative analysis of liver fat content (LFC) in patients with the suspicion of fatty liver disease using histopathology as the standard of reference.

A 20-channel receive-only mouse array coil for a 3 T clinical MRI system

A 20-channel phased-array coil for MRI of mice has been designed, constructed, and validated with bench measurements and high-resolution accelerated imaging. The technical challenges of designing a small, high density array have been overcome using individual small-diameter coil elements arranged on a cylinder in a hexagonal overlapping design with adjacent low impedance preamplifiers to further decouple the array elements. Signal-to-noise ratio (SNR) and noise amplification in accelerated imaging were simulated and quantitatively evaluated in phantoms and in vivo mouse images. Comparison between the 20-channel mouse array and a length-matched quadrature driven small animal birdcage coil showed an SNR increase at the periphery and in the center of the phantom of 3- and 1.3-fold, respectively. Comparison with a shorter but SNR-optimized birdcage coil (aspect ratio 1:1 and only half mouse coverage) showed an SNR gain of twofold at the edge of the phantom and similar SNR in the center. G-factor measurements indicate that the coil is well suited to acquire highly accelerated images.

Gradient estimation in dendritic reinforcement learning

We study synaptic plasticity in a complex neuronal cell model where NMDA-spikes can arise in certain dendritic zones. In the context of reinforcement learning, two kinds of plasticity rules are derived, zone reinforcement (ZR) and cell reinforcement (CR), which both optimize the expected reward by stochastic gradient ascent. For ZR, the synaptic plasticity response to the external reward signal is modulated exclusively by quantities which are local to the NMDA-spike initiation zone in which the synapse is situated. CR, in addition, uses nonlocal feedback from the soma of the cell, provided by mechanisms such as the backpropagating action potential. Simulation results show that, compared to ZR, the use of nonlocal feedback in CR can drastically enhance learning performance. We suggest that the availability of nonlocal feedback for learning is a key advantage of complex neurons over networks of simple point neurons, which have previously been found to be largely equivalent with regard to computational capability.