Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering

Purpose To investigate whether nonlinear dimensionality reduction improves unsupervised classification of 1H MRS brain tumor data compared with a linear method. Methods In vivo single-voxel 1H magnetic resonance spectroscopy (55 patients) and 1H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. Results An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With 1H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. Conclusion Purpose To investigate whether nonlinear dimensionality reduction improves unsupervised classification of 1H MRS brain tumor data compared with a linear method. Methods In vivo single-voxel 1H magnetic resonance spectroscopy (55 patients) and 1H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. Results An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With 1H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. Conclusion The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of 1H MRSI data after cluster analysis

Torque-planning errors affect the perception of object properties and sensorimotor memories during object manipulation in uncertain grasp situations.

This is the author accepted manuscript. The final version is available from American Physiological Society via the DOI in this record.Predicting instead of only reacting to the properties of objects we grasp is crucial to dexterous object manipulation. Although we normally plan our grasps according to well-learned associations, we rely on implicit sensorimotor memories when we learn to interact with novel or ambiguous objects. However, little is known about the influence of sensorimotor predictions on subsequent perception and action. Here, young and elderly subjects repeatedly lifted an object in which the center of mass (CoM) was randomly varied between trials straight upward with the aim of preventing object tilts. After each lift, subjects indicated the location of the perceived CoM and reported how heavy the object felt. Surprisingly, we found that sensorimotor torque memories eventually causing initial lifting errors had substantial effects on the perception of torques, weight, and the torque planning for the next lift. Whereas subjects tended to partly retain their previous erroneous sensorimotor memories (instead of solely relying on the previously encountered torque for the upcoming motor plan), they perceived encountered torques to be stronger when they erroneously predicted them. Additionally, we found that torque prediction errors, as well as the actual torques, made the object feel heavier. By contrast, perception did not influence upcoming motor control. There were no major differences observed between the age groups. The sensorimotor impact on torque perception can be explained by internal feedforward prediction highlighting task-relevant errors, while the partial retention and adaptation of sensorimotor torque memories is reconciled with the trial-to-trial learning rule for motor adaptation. NEW & NOTEWORTHY The current study is the first to demonstrate in an object manipulation task in uncertainty that errors in the sensorimotor prediction of torques influence the perception of both torques and weight, whereas sensorimotor torque memories are partly retained and partly adapted to planning errors. Our results provide novel insights into the predictive mechanisms underpinning the common everyday task of object manipulation and further support theories about the predictive modulation of perception established in other neuroscientific disciplines

The Shapes of Cooperatively Rearranging Regions in Glass Forming Liquids

The shapes of cooperatively rearranging regions in glassy liquids change from being compact at low temperatures to fractal or ``stringy'' as the dynamical crossover temperature from activated to collisional transport is approached from below. We present a quantitative microscopic treatment of this change of morphology within the framework of the random first order transition theory of glasses. We predict a correlation of the ratio of the dynamical crossover temperature to the laboratory glass transition temperature, and the heat capacity discontinuity at the glass transition, Delta C_p. The predicted correlation agrees with experimental results for the 21 materials compiled by Novikov and Sokolov.Comment: 9 pages, 6 figure

Non-monotonic temperature evolution of dynamic correlations in glass-forming liquids

The viscosity of glass-forming liquids increases by many orders of magnitude if their temperature is lowered by a mere factor of 2-3 [1,2]. Recent studies suggest that this widespread phenomenon is accompanied by spatially heterogeneous dynamics [3,4], and a growing dynamic correlation length quantifying the extent of correlated particle motion [5-7]. Here we use a novel numerical method to detect and quantify spatial correlations which reveal a surprising non-monotonic temperature evolution of spatial dynamical correlations, accompanied by a second length scale that grows monotonically and has a very different nature. Our results directly unveil a dramatic qualitative change in atomic motions near the mode-coupling crossover temperature [8] which involves no fitting or indirect theoretical interpretation. Our results impose severe new constraints on the theoretical description of the glass transition, and open several research perspectives, in particular for experiments, to confirm and quantify our observations in real materials.Comment: 7 page

Practical quantum metrology in noisy environments

This is the final version. Available from American Physical Society via the DOI in this recordThe problem of estimating an unknown phase φ using two-level probes in the presence of unital phase-covariant noise and using finite resources is investigated. We introduce a simple model in which the phase-imprinting operation on the probes is realized by a unitary transformation with a randomly sampled generator. We determine the optimal phase sensitivity in a sequential estimation protocol and derive a general (tight-fitting) lower bound. The sensitivity grows quadratically with the number of applications N of the phase-imprinting operation, then attains a maximum at some N opt , and eventually decays to zero. We provide an estimate of N opt in terms of accessible geometric properties of the noise and illustrate its usefulness as a guideline for optimizing the estimation protocol. The use of passive ancillas and of entangled probes in parallel to improve the phase sensitivity is also considered. We find that multiprobe entanglement may offer no practical advantage over single-probe coherence if the interrogation at the output is restricted to measuring local observables.European Research CouncilRoyal Societ

Large 21 cm signals from AGN-dominated reionization

We present predictions for the spatial distribution of 21-cm brightness temperature fluctuations from high-dynamic-range simulations for active galactic nucleus (AGN)-dominated reionization histories that have been tested against available Ly$\alpha$ and cosmic microwave background (CMB) data. We model AGNs by extrapolating the observed $M_\text{bh}$ − σ relation to high redshifts and assign them ionizing emissivities consistent with recent UV luminosity function measurements. We assess the observability of the predicted spatial 21-cm fluctuations in the late stages of reionization in the limit in which the hydrogen 21-cm spin temperature is significantly larger than the CMB temperature. Our AGN-dominated reionization histories increase the variance of the 21-cm emission by a factor of up to 10 compared to similar reionization histories dominated by faint galaxies, to values close to 100 mK$^2$ at scales accessible to experiments ($k$ $\lesssim$ 1 cMpc$^{−1}$ $h$). This is lower than the sensitivity reached by ongoing experiments only by a factor of about 2 or less. When reionization is dominated by AGNs, the 21-cm power spectrum is enhanced on all scales due to the enhanced bias of the clustering of the more massive haloes and the peak in the large scale 21-cm power is strongly enhanced and moved to larger scales due to bigger characteristic bubble sizes. AGN-dominated reionization should be easily detectable by Low Frequency Array (and later Hydrogen Epoch of Reionization Array and Phase 1 of the Square Kilometre Array) at their design sensitivity, assuming successful foreground subtraction and instrument calibration. Conversely, these could become the first non-trivial reionization scenarios to be ruled out by 21-cm experiments, thereby constraining the contribution of AGNs to reionization.Support by ERC Advanced grant 320596 ‘The Emergence of Structure During the Epoch of Reionization’ is gratefully acknowledged. EP gratefully acknowledges support by the Kavli Foundation. We acknowledge PRACE for awarding us access to the Curie supercomputer, based in France at the Tres Grand Centre de Calcul ´ (TGCC). This work used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). This equipment was funded by BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grants ST/H008519/1 and ST/K00087X/1, STFC DiRAC Operations grant ST/K003267/1 and Durham University. DiRAC is part of the National E-Infrastructure. This research was supported by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence ‘Origin and Structure of the Universe’

Evolution of the Quasar Luminosity Function: Implications for EoR-21cm

AbstractWe present predictions for the spatial distribution of 21 cm brightness temperature fluctuations from high-dynamic-range simulations for AGN-dominated reionization histories that have been tested against available Lyα and CMB data. We model AGN by extrapolating the observed Mbh–σ relation to high redshifts and assign them ionizing emissivities consistent with recent UV luminosity function measurements. AGN-dominated reionization histories increase the variance of the 21 cm emission by a factor of up to ten compared to similar reionization histories dominated by faint galaxies, to values close to 100 mK2 at scales accessible to experiments (k ≲ 1 cMpc−1h). This is lower than the sensitivity reached by ongoing experiments by only a factor of about two or less. AGN dominated reionization should be easily detectable by LOFAR (and later HERA and SKA1) at their design sensitivity.</jats:p

Crystal growth and quantum oscillations in the topological chiral semimetal CoSi

We survey the electrical transport properties of the single-crystalline, topological chiral semimetal CoSi which was grown via different methods. High-quality CoSi single crystals were found in the growth from tellurium solution. The sample's high carrier mobility enables us to observe, for the first time, quantum oscillations (QOs) in its thermoelectrical signals. Our analysis of QOs reveals two spherical Fermi surfaces around the R point in the Brillouin zone corner. The extracted Berry phases of these electron orbits are consistent with the -2 chiral charge as reported in DFT calculations. Detailed analysis on the QOs reveals that the spin-orbit coupling induced band-splitting is less than 2 meV near the Fermi level, one order of magnitude smaller than our DFT calculation result. We also report the phonon-drag induced large Nernst effect in CoSi at intermediate temperatures