Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

Temperature influences dynamics and state-equilibrium distributions in all molecular processes, and only a relatively narrow range of temperatures is compatible with life—organisms must avoid temperature extremes that can cause physical damage or metabolic disruption. Animals evolved a set of sensory ion channels, many of them in the family of transient receptor potential cation channels that detect biologically relevant changes in temperature with remarkable sensitivity. Depending on the specific ion channel, heating or cooling elicits conformational changes in the channel to enable the flow of cations into sensory neurons, giving rise to electrical signaling and sensory perception. The molecular mechanisms responsible for the heightened temperature-sensitivity in these ion channels, as well as the molecular adaptations that make each channel specifically heat- or cold-activated, are largely unknown. It has been hypothesized that a heat capacity difference (ΔC p ) between two conformational states of these biological thermosensors can drive their temperature-sensitivity, but no experimental measurements of ΔC p have been achieved for these channel proteins. Contrary to the general assumption that the ΔC p is constant, measurements from soluble proteins indicate that the ΔC p is likely to be a function of temperature. By investigating the theoretical consequences for a linearly temperature-dependent ΔC p on the open–closed equilibrium of an ion channel, we uncover a range of possible channel behaviors that are consistent with experimental measurements of channel activity and that extend beyond what had been generally assumed to be possible for a simple two-state model, challenging long-held assumptions about ion channel gating models at equilibrium.

A methodology based on the transistor body effect is used to monitor inversion oxide thicknesses (T inv 's) in high-κ/metal-gate undoped ultrathin-body short-channel SOI FINFETs. The extracted T inv 's are benchmarked to independent capacitance-voltage (C-V ) measurements. For the first time, device simulation is introduced to understand the fundamental difference in T inv values extracted using the two techniques, which is driven by the inversion charge centroid at different bias conditions. Index Terms-Fully depleted SOI (FDSOI), FINFETs, inversion oxide thickness, ultrathin body.

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