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Abstract The brain can be decomposed into large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. We have developed theNetwork Correspondence Toolbox(NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and multiple widely used functional brain atlases. We provide several exemplar demonstrations to illustrate how researchers can use the NCT to report their own findings. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights. 

We present a simple and effective method to create highly entangled spin states on a faster timescale than that of the commonly employed one-axis twisting (OAT) model. We demonstrate that by periodically driving the Dicke Hamiltonian at a resonance frequency, the system effectively becomes a two-axis countertwisting Hamiltonian, which is known to quickly create Heisenberg limit scaled entangled states. For these states we show that simple quadrature measurements can saturate the ultimate precision limit for parameter estimation determined by the quantum Cramér-Rao bound. An example experimental realization of the periodically driven scheme is discussed with the potential to quickly generate momentum entanglement in a recently described experimental vertical cavity system. We analyze effects of collective dissipation in this vertical cavity system and find that our squeezing protocol can be more robust than the previous realization of OAT. Published by the American Physical Society2024 

Abstract The signal amplification by reversible exchange process (SABRE) enhances NMR signals by unlocking hidden polarization in parahydrogen through interactions with to-be-hyperpolarized substrate molecules when both are transiently bound to an Ir-based organometallic catalyst. Recent efforts focus on optimizing polarization transfer from parahydrogen-derived hydride ligands to the substrate in SABRE. However, this requires quantitative information on ligand exchange rates, which common NMR techniques struggle to provide. Here, we introduce an experimental spin order transfer sequence, with readout occurring at¹⁵N nuclei directly interacting with the catalyst. Enhanced¹⁵N NMR signals overcome sensitivity challenges, encoding substrate dissociation rates. This methodology enables robust data fitting to ligand exchange models, yielding substrate dissociation rate constants with higher precision than classical 1D and 2D¹H NMR approaches. This refinement improves the accuracy of key activation enthalpy ΔH^‡and entropy ΔS^‡estimates. Furthermore, the higher chemical shift dispersion provided by enhanced¹⁵N NMR reveals the kinetics of substrate dissociation for acetonitrile and metronidazole, previously inaccessible via¹H NMR due to small chemical shift differences between free and Ir-bound substrates. The presented approach can be successfully applied not only to isotopically enriched substrates but also to compounds with natural abundance of the to-be-hyperpolarized heteronuclei.