Neuroradiologists and neurosurgeons increasingly opt to use functional magnetic resonance imaging (fMRI) to map functionally relevant brain regions for noninvasive presurgical planning and intraoperative neuronavigation. This application requires a high degree of spatial accuracy, but the fMRI signal-to-noise ratio (SNR) decreases as spatial resolution increases. In practice, fMRI scans can be collected at multiple spatial resolutions, and it is of interest to make more accurate inference on brain activity by combining data with different resolutions. To this end, we develop a new Bayesian model to leverage both better anatomical precision in high resolution fMRI and higher SNR in standard resolution fMRI. We assign a Gaussian process prior to the mean intensity function and develop an efficient, scalable posterior computation algorithm to integrate both sources of data. We draw posterior samples using an algorithm analogous to Riemann manifold Hamiltonian Monte Carlo in an expanded parameter space. We illustrate our method in analysis of presurgical fMRI data, and show in simulation that it infers the mean intensity more accurately than alternatives that use either the high or standard resolution fMRI data alone.

Bayesian inference for brain activity from functional magnetic resonance imaging collected at two spatial resolutions

: One of the most versatile sources for entangled photons are emitters that interact via more than one tunable mechanism. Here, we demonstrate how hybridization and dipole-dipole interactions—potentially simultaneously available in colloidal quantum dots and molecular aggregates—leveraged in conjunction can couple simple, well understood emitters into composite emitters with flexible control over the level structure. We show that cascade decay through carefully designed level structures can result in emission of frequency-entangled photons with Bell states and three-photon GHZ states as example cases. These results pave the way toward rational design of quantum optical emitters of entangled photons.

Entangled photons from composite cascade emitters

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Bayesian inference for brain activity from functional magnetic resonance imaging collected at two spatial resolutions

Entangled photons from composite cascade emitters