Integrated Calendar

Diffusion MRI is an excellent method for detecting subtle microscopic changes of the living human brain, but often fails to assign the experimental observations to specific structural properties such as cell density, size, shape, or orientation. When attempting to solve this problem, we have chosen to disregard essentially all previous work in the field of diffusion MRI, and instead translate data acquisition and processing schemes from multidimensional solid-state NMR spectroscopy [1, 2]. Key elements of our approach are q-vector trajectories and correlations between isotropic and directional diffusion encoding. By approximating the water displacement probability as a sum of anisotropic Gaussians, the voxel composition can be reported as a diffusion tensor distribution where each component of the distribution corresponds to a distinct tissue environment. Our new methods yield estimates of the complete diffusion tensor distribution or well-defined statistical properties thereof, such as the mean and variance of isotropic diffusivities, mean-square anisotropy, and orientational order parameter, which derive from analogous parameters in solid-state NMR and can be related to the structural properties of the tissue. This presentation will give an overview of the new methods, including basic physical principles, pulse sequences, and data processing, as well as examples of applications in soft matter systems from lipid membranes to living brains

Diffusion MRI is an excellent method for detecting subtle microscopic changes of the living human brain, but often fails to assign the experimental observations to specific structural properties such as cell density, size, shape, or orientation. When attempting to solve this problem, we have chosen to disregard essentially all previous work in the field of diffusion MRI, and instead translate data acquisition and processing schemes from multidimensional solid-state NMR spectroscopy [1, 2]. Key elements of our approach are q-vector trajectories and correlations between isotropic and directional diffusion encoding. By approximating the water displacement probability as a sum of anisotropic Gaussians, the voxel composition can be reported as a diffusion tensor distribution where each component of the distribution corresponds to a distinct tissue environment. Our new methods yield estimates of the complete diffusion tensor distribution or well-defined statistical properties thereof, such as the mean and variance of isotropic diffusivities, mean-square anisotropy, and orientational order parameter, which derive from analogous parameters in solid-state NMR and can be related to the structural properties of the tissue. This presentation will give an overview of the new methods, including basic physical principles, pulse sequences, and data processing, as well as examples of applications in soft matter systems from lipid membranes to living brains.

Einstein formulated general relativity just over 100 years ago. Although it is generally considered a great triumph, the theory's early years were characterized by conceptual confusion, empirical uncertainties and a lack of relevance to ordinary physics. But in recent decades, a remarkably diverse set of precision experiments has established it as the

Strong light-matter interactions in microcavities have been long known to provide means to alter optical and nonlinear properties of the coupled system. As a result of this interaction, one typically observes the emergence of new polaritonic eigenstates of the coupled system. These states are of hybrid nature and possess both light and matter characteristics, which is reflected as so-called vacuum Rabi splitting, observed in the absorption or transmission spectra. Because of the hybrid nature of these states, the excited state temporal dynamics can be significantly altered in comparison to the uncoupled system dynamics. This, in turn, can have profound effects on the emission and photochemical processes.
In this talk I will discuss our recent results on individual plasmonic nanoantennas strongly coupled to molecular J-aggregates 1-4 and 2D materials 5. In the case of J-aggregates we observe Rabi splitting up to 400 meV, i.e. ~20% of the resonance energy. Moreover, we observe mode splitting not only in elastic scattering but also in photoluminescence of individual hybrid nanosystems, which manifests a direct proof of strong coupling in plasmon-exciton nanoparticles. This situation is drastically different from the photoluminescence of uncoupled molecules, which signals the involvement of polaritonic states into the relaxation pathways of the hybrid system. I also discuss how the involvement of these pathways can modify other relevant excited state dynamics, including photo-oxidation processes 4. In the case of 2D materials, we observe complex temperate-dependent plasmon-exciton polariton mixtures, which at low temperatures can admix trions (charged excitons) into a common polaritonic state (see Figure below) 5. Such admixture can be interesting in the context of polariton-polariton interactions and potentially for the charge transport in strongly coupled systems.

Over the course of a natural day-night cycle, mean luminance levels can span ten log units or more. Mammalian retinas effectively encode visual information over this vast range, in part by utilizing exquisitely sensitive rod photoreceptors in dim conditions and multiple color-variant cone photoreceptors in bright conditions. These visual signals, regardless of origin, must pass through a common set of retinal ganglion cells, thereby creating opportunities for signal interactions. Human perceptual experiments conducted under intermediate lighting conditions reveal constructive and destructive interactions between flickering rod and cone stimuli that are thought to originate in the retina. In support of this hypothesis, we find rod-cone flicker interference in On and Off retinal ganglion cells that project! to magnocellular visual pathways in primates. The dependence of this interference on the frequency and phase of the temporal modulation is similar to that observed in perceptual measurements. Recordings from within the retinal circuitry indicate that rod-cone signal interference reflects a linear combination of kinetically-distinct rod and cone signals upstream of the ganglion cell synaptic inputs. Ultimately, using our empirically-derived data as a foundation, we construct a mathematical model that recapitulates known rod-cone interactions and predicts retinal output in response to a broad range of time-varying rod and cone stimuli.