Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method.

The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.

Exciton Proliferation and Fate of the Topological Mott Insulator in a Twisted Bilayer Graphene Lattice Model.

A topological Mott insulator (TMI) with spontaneous time-reversal symmetry breaking and nonzero Chern number has been discovered in a real-space effective model for twisted bilayer graphene (TBG) at 3/4 filling in the strong coupling limit [1]. However, the finite temperature properties of such a TMI state remain illusive. In this work, employing the state-of-the-art thermal tensor network and the perturbative field-theoretical approaches, we obtain the finite-T phase diagram and the dynamical properties of the TBG model. The phase diagram includes the quantum anomalous Hall and charge density wave phases at low T, and an Ising transition separating them from the high-T symmetric phases. Because of the proliferation of excitons-particle-hole bound states-the transitions take place at a significantly reduced temperature than the mean-field estimation. The exciton phase is accompanied with distinctive experimental signatures in such as in charge compressibilities and optical conductivities close to the transition. Our work explains the smearing of the many-electron state topology by proliferating excitons and opens an avenue for controlled many-body investigations on finite-temperature states in the TBG and other quantum moiré systems.