Header logo is


2019


Thumb xl superconducting
Soft-magnetic coatings as possible sensors for magnetic imaging of superconductors

Ionescu, A., Simmendinger, J., Bihler, M., Miksch, C., Fischer, P., Soltan, S., Schütz, G., Albrecht, J.

Supercond. Sci. and Tech., 33, pages: 015002, IOP, December 2019 (article)

Abstract
Magnetic imaging of superconductors typically requires a soft-magnetic material placed on top of the superconductor to probe local magnetic fields. For reasonable results the influence of the magnet onto the superconductor has to be small. Thin YBCO films with soft-magnetic coatings are investigated using SQUID magnetometry. Detailed measurements of the magnetic moment as a function of temperature, magnetic field and time have been performed for different heterostructures. It is found that the modification of the superconducting transport in these heterostructures strongly depends on the magnetic and structural properties of the soft-magnetic material. This effect is especially pronounced for an inhomogeneous coating consisting of ferromagnetic nanoparticles.

pf mms

link (url) DOI [BibTex]

2019


link (url) DOI [BibTex]


Thumb xl array hologram
Acoustic hologram enhanced phased arrays for ultrasonic particle manipulation

Cox, L., Melde, K., Croxford, A., Fischer, P., Drinkwater, B.

Phys. Rev. Applied, 12, pages: 064055, November 2019 (article)

Abstract
The ability to shape ultrasound fields is important for particle manipulation, medical therapeutics and imaging applications. If the amplitude and/or phase is spatially varied across the wavefront then it is possible to project ‘acoustic images’. When attempting to form an arbitrary desired static sound field, acoustic holograms are superior to phased arrays due to their significantly higher phase fidelity. However, they lack the dynamic flexibility of phased arrays. Here, we demonstrate how to combine the high-fidelity advantages of acoustic holograms with the dynamic control of phased arrays in the ultrasonic frequency range. Holograms are used with a 64-element phased array, driven with continuous excitation. Moving the position of the projected hologram via phase delays which steer the output beam is demonstrated experimentally. This allows the creation of a much more tightly focused point than with the phased array alone, whilst still being reconfigurable. It also allows the complex movement at a water-air interface of a “phase surfer” along a phase track or the manipulation of a more arbitrarily shaped particle via amplitude traps. Furthermore, a particle manipulation device with two emitters and a single split hologram is demonstrated that allows the positioning of a “phase surfer” along a 1D axis. This paper opens the door for new applications with complex manipulation of ultrasound whilst minimising the complexity and cost of the apparatus.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl micropropeller
A Helical Microrobot with an Optimized Propeller-Shape for Propulsion in Viscoelastic Biological Media

Li., D., Jeong, M., Oren, E., Yu, T., Qiu, T.

Robotics, 8, pages: 87, MDPI, October 2019 (article)

Abstract
One major challenge for microrobots is to penetrate and effectively move through viscoelastic biological tissues. Most existing microrobots can only propel in viscous liquids. Recent advances demonstrate that sub-micron robots can actively penetrate nanoporous biological tissue, such as the vitreous of the eye. However, it is still difficult to propel a micron-sized device through dense biological tissue. Here, we report that a special twisted helical shape together with a high aspect ratio in cross-section permit a microrobot with a diameter of hundreds-of-micrometers to move through mouse liver tissue. The helical microrobot is driven by a rotating magnetic field and localized by ultrasound imaging inside the tissue. The twisted ribbon is made of molybdenum and a sharp tip is chemically etched to generate a higher pressure at the edge of the propeller to break the biopolymeric network of the dense tissue.

pf

link (url) DOI [BibTex]


Thumb xl cell patterning with acoustic hologram
Acoustic Holographic Cell Patterning in a Biocompatible Hydrogel

Ma, Z., Holle, A., Melde, K., Qiu, T., Poeppel, K., Kadiri, V., Fischer, P.

Adv. Mat., October 2019 (article)

Abstract
Acoustophoresis is promising as a rapid, biocompatible, non-contact cell manipulation method, where cells are arranged along the nodes or antinodes of the acoustic field. Typically, the acoustic field is formed in a resonator, which results in highly symmetric regular patterns. However, arbitrary, non-symmetrically shaped cell assemblies are necessary to obtain the irregular cellular arrangements found in biological tissues. We show that arbitrarily shaped cell patterns can be obtained from the complex acoustic field distribution defined by an acoustic hologram. Attenuation of the sound field induces localized acoustic streaming and the resultant convection flow gently delivers the suspended cells to the image plane where they form the designed pattern. We show that the process can be implemented in a biocompatible collagen solution, which can then undergo gelation to immobilize the cell pattern inside the viscoelastic matrix. The patterned cells exhibit F-actin-based protrusions, which indicates that the cells grow and thrive within the matrix. Cell viability assays and brightfield imaging after one week confirm cell survival and that the patterns persist. Acoustophoretic cell manipulation by holographic fields thus holds promise for non-contact, long-range, long-term cellular pattern formation, with a wide variety of potential applications in tissue engineering and mechanobiology.

pf

link (url) DOI [BibTex]


Thumb xl phantom surgery
A High-Fidelity Phantom for the Simulation and Quantitative Evaluation of Transurethral Resection of the Prostate

Choi, E., Adams, F., Gengenbacher, A., Schlager, D., Palagi, S., Müller, P., Wetterauer, U., Miernik, A., Fischer, P., Qiu, T.

Annals of Biomed. Eng., October 2019 (article)

Abstract
Transurethral resection of the prostate (TURP) is a minimally invasive endoscopic procedure that requires experience and skill of the surgeon. To permit surgical training under realistic conditions we report a novel phantom of the human prostate that can be resected with TURP. The phantom mirrors the anatomy and haptic properties of the gland and permits quantitative evaluation of important surgical performance indicators. Mixtures of soft materials are engineered to mimic the physical properties of the human tissue, including the mechanical strength, the electrical and thermal conductivity, and the appearance under an endoscope. Electrocautery resection of the phantom closely resembles the procedure on human tissue. Ultrasound contrast agent was applied to the central zone, which was not detectable by the surgeon during the surgery but showed high contrast when imaged after the surgery, to serve as a label for the quantitative evaluation of the surgery. Quantitative criteria for performance assessment are established and evaluated by automated image analysis. We present the workflow of a surgical simulation on a prostate phantom followed by quantitative evaluation of the surgical performance. Surgery on the phantom is useful for medical training, and enables the development and testing of endoscopic and minimally invasive surgical instruments.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl vision
Interactive Materials – Drivers of Future Robotic Systems

Fischer, P.

Adv. Mat., October 2019 (article)

Abstract
A robot senses its environment, processes the sensory information, acts in response to these inputs, and possibly communicates with the outside world. Robots generally achieve these tasks with electronics-based hardware or by receiving inputs from some external hardware. In contrast, simple microorganisms can autonomously perceive, act, and communicate via purely physicochemical processes in soft material systems. A key property of biological systems is that they are built from energy-consuming ‘active’ units. Exciting developments in material science show that even very simple artificial active building blocks can show surprisingly rich emergent behaviors. Active non-equilibrium systems are therefore predicted to play an essential role to realize interactive materials. A major challenge is to find robust ways to couple and integrate the energy-consuming building blocks to the mechanical structure of the material. However, success in this endeavor will lead to a new generation of sophisticated micro- and soft-robotic systems that can operate autonomously.

pf

[BibTex]


Thumb xl plasmonic dimers
Arrays of plasmonic nanoparticle dimers with defined nanogap spacers

Jeong, H., Adams, M. C., Guenther, J., Alarcon-Correa, M., Kim, I., Choi, E., Miksch, C., Mark, A. F. M., Mark, A. G., Fischer, P.

ACS Nano, September 2019 (article)

Abstract
Plasmonic molecules are building blocks of metallic nanostructures that give rise to intriguing optical phenomena with similarities to those seen in molecular systems. The ability to design plasmonic hybrid structures and molecules with nanometric resolution would enable applications in optical metamaterials and sensing that presently cannot be demonstrated, because of a lack of suitable fabrication methods allowing the structural control of the plasmonic atoms on a large scale. Here we demonstrate a wafer-scale “lithography-free” parallel fabrication scheme to realize nanogap plasmonic meta-molecules with precise control over their size, shape, material, and orientation. We demonstrate how we can tune the corresponding coupled resonances through the entire visible spectrum. Our fabrication method, based on glancing angle physical vapor deposition with gradient shadowing, permits critical parameters to be varied across the wafer and thus is ideally suited to screen potential structures. We obtain billions of aligned dimer structures with controlled variation of the spectral properties across the wafer. We spectroscopically map the plasmonic resonances of gold dimer structures and show that they not only are in good agreement with numerically modeled spectra, but also remain functional, at least for a year, in ambient conditions.

pf

link (url) DOI [BibTex]


no image
Convolutional neural networks: A magic bullet for gravitational-wave detection?

Gebhard, T., Kilbertus, N., Harry, I., Schölkopf, B.

Physical Review D, 100(6):063015, American Physical Society, September 2019 (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Data scarcity, robustness and extreme multi-label classification

Babbar, R., Schölkopf, B.

Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl enzyme nanonets toc
Genetically modified M13 bacteriophage nanonets for enzyme catalysis and recovery

Kadiri, V. M., Alarcon-Correa, M., Guenther, J. P., Ruppert, J., Bill, J., Rothenstein, D., Fischer, P.

Catalysts, 9, pages: 723, August 2019 (article)

Abstract
Enzyme-based biocatalysis exhibits multiple advantages over inorganic catalysts, including the biocompatibility and the unchallenged specificity of enzymes towards their substrate. The recovery and repeated use of enzymes is essential for any realistic application in biotechnology, but is not easily achieved with current strategies. For this purpose, enzymes are often immobilized on inorganic scaffolds, which could entail a reduction of the enzymes’ activity. Here, we show that immobilization to a nano-scaled biological scaffold, a nanonetwork of end-to-end cross-linked M13 bacteriophages, ensures high enzymatic activity and at the same time allows for the simple recovery of the enzymes. The bacteriophages have been genetically engineered to express AviTags at their ends, which permit biotinylation and their specific end-to-end self-assembly while allowing space on the major coat protein for enzyme coupling. We demonstrate that the phages form nanonetwork structures and that these so-called nanonets remain highly active even after re-using the nanonets multiple times in a flow-through reactor.

pf

link (url) DOI [BibTex]


Thumb xl special issue adv opt mat
Light-controlled micromotors and soft microrobots

Palagi, S., Singh, D. P., Fischer, P.

Adv. Opt. Mat., 7, pages: 1900370, August 2019 (article)

Abstract
Mobile microscale devices and microrobots can be powered by catalytic reactions (chemical micromotors) or by external fields. This report is focused on the role of light as a versatile means for wirelessly powering and controlling such microdevices. Recent advances in the development of autonomous micromotors are discussed, where light permits their actuation with unprecedented control and thereby enables advances in the field of active matter. In addition, structuring the light field is a new means to drive soft microrobots that are based on (photo‐) responsive polymers. The behavior of the two main classes of thermo‐ and photoresponsive polymers adopted in microrobotics (poly(N‐isopropylacrylamide) and liquid‐crystal elastomers) is analyzed, and recent applications are reported. The advantages and limitations of controlling micromotors and microrobots by light are reviewed, and some of the remaining challenges in the development of novel photo‐active materials for micromotors and microrobots are discussed.

pf

link (url) DOI [BibTex]


Thumb xl paper images.006
Learning Variable Impedance Control for Contact Sensitive Tasks

Bogdanovic, M., Khadiv, M., Righetti, L.

arXiv preprint, arXiv:1907.07500, July 2019 (article)

Abstract
Reinforcement learning algorithms have shown great success in solving different problems ranging from playing video games to robotics. However, they struggle to solve delicate robotic problems, especially those involving contact interactions. Though in principle a policy outputting joint torques should be able to learn these tasks, in practice we see that they have difficulty to robustly solve the problem without any structure in the action space. In this paper, we investigate how the choice of action space can give robust performance in presence of contact uncertainties. We propose to learn a policy that outputs impedance and desired position in joint space as a function of system states without imposing any other structure to the problem. We compare the performance of this approach to torque and position control policies under different contact uncertainties. Extensive simulation results on two different systems, a hopper (floating-base) with intermittent contacts and a manipulator (fixed-base) wiping a table, show that our proposed approach outperforms policies outputting torque or position in terms of both learning rate and robustness to environment uncertainty.

mg

[BibTex]


Thumb xl m13 bacteriophages
Self-Assembled Phage-Based Colloids for High Localized Enzymatic Activity

Alarcon-Correa, M., Guenther, J., Troll, J., Kadiri, V. M., Bill, J., Fischer, P., Rothenstein, D.

ACS Nano, March 2019 (article)

Abstract
Catalytically active colloids are model systems for chemical motors and active matter. It is desirable to replace the inorganic catalysts and the toxic fuels that are often used, with biocompatible enzymatic reactions. However, compared to inorganic catalysts, enzyme-coated colloids tend to exhibit less activity. Here, we show that the self-assembly of genetically engineered M13 bacteriophages that bind enzymes to magnetic beads ensures high and localized enzymatic activity. These phage-decorated colloids provide a proteinaceous environment for directed enzyme immobilization. The magnetic properties of the colloidal carrier particle permit repeated enzyme recovery from a reaction solution, while the enzymatic activity is retained. Moreover, localizing the phage-based construct with a magnetic field in a microcontainer allows the enzyme-phage-colloids to function as an enzymatic micropump, where the enzymatic reaction generates a fluid flow. This system shows the fastest fluid flow reported to date by a biocompatible enzymatic micropump. In addition, it is functional in complex media including blood where the enzyme driven micropump can be powered at the physiological blood-urea concentration.

pf

link (url) DOI [BibTex]


Thumb xl jcp pfg nmr
Absolute diffusion measurements of active enzyme solutions by NMR

Guenther, J., Majer, G., Fischer, P.

J. Chem. Phys., 150(124201), March 2019 (article)

Abstract
The diffusion of enzymes is of fundamental importance for many biochemical processes. Enhanced or directed enzyme diffusion can alter the accessibility of substrates and the organization of enzymes within cells. Several studies based on fluorescence correlation spectroscopy (FCS) report enhanced diffusion of enzymes upon interaction with their substrate or inhibitor. In this context, major importance is given to the enzyme fructose-bisphosphate aldolase, for which enhanced diffusion has been reported even though the catalysed reaction is endothermic. Additionally, enhanced diffusion of tracer particles surrounding the active aldolase enzymes has been reported. These studies suggest that active enzymes can act as chemical motors that self-propel and give rise to enhanced diffusion. However, fluorescence studies of enzymes can, despite several advantages, suffer from artefacts. Here we show that the absolute diffusion coefficients of active enzyme solutions can be determined with Pulsed Field Gradient Nuclear Magnetic Resonance (PFG-NMR). The advantage of PFG-NMR is that the motion of the molecule of interest is directly observed in its native state without the need for any labelling. Further, PFG-NMR is model-free and thus yields absolute diffusion constants. Our PFG-NMR experiments of solutions containing active fructose-bisphosphate aldolase from rabbit muscle do not show any diffusion enhancement for the active enzymes nor the surrounding molecules. Additionally, we do not observe any diffusion enhancement of aldolase in the presence of its inhibitor pyrophosphate.

pf

link (url) DOI [BibTex]


Thumb xl activeoptorheologicalmedium
Chemical Nanomotors at the Gram Scale Form a Dense Active Optorheological Medium

Choudhury, U., Singh, D. P., Qiu, T., Fischer, P.

Adv. Mat., (1807382), Febuary 2019 (article)

Abstract
The rheological properties of a colloidal suspension are a function of the concentration of the colloids and their interactions. While suspensions of passive colloids are well studied and have been shown to form crystals, gels, and glasses, examples of energy‐consuming “active” colloidal suspensions are still largely unexplored. Active suspensions of biological matter, such as motile bacteria or dense mixtures of active actin–motor–protein mixtures have, respectively, reveals superfluid‐like and gel‐like states. Attractive inanimate systems for active matter are chemically self‐propelled particles. It has so far been challenging to use these swimming particles at high enough densities to affect the bulk material properties of the suspension. Here, it is shown that light‐triggered asymmetric titanium dioxide that self‐propel, can be obtained in large quantities, and self‐organize to make a gram‐scale active medium. The suspension shows an activity‐dependent tenfold reversible change in its bulk viscosity.

pf

link (url) DOI [BibTex]


Thumb xl hyperrayleigh
First Observation of Optical Activity in Hyper-Rayleigh Scattering

Collins, J., Rusimova, K., Hooper, D., Jeong, H. H., Ohnoutek, L., Pradaux-Caggiano, F., Verbiest, T., Carbery, D., Fischer, P., Valev, V.

Phys. Rev. X, 9(011024), January 2019 (article)

Abstract
Chiral nano- or metamaterials and surfaces enable striking photonic properties, such as negative refractive index and superchiral light, driving promising applications in novel optical components, nanorobotics, and enhanced chiral molecular interactions with light. In characterizing chirality, although nonlinear chiroptical techniques are typically much more sensitive than their linear optical counterparts, separating true chirality from anisotropy is a major challenge. Here, we report the first observation of optical activity in second-harmonic hyper-Rayleigh scattering (HRS). We demonstrate the effect in a 3D isotropic suspension of Ag nanohelices in water. The effect is 5 orders of magnitude stronger than linear optical activity and is well pronounced above the multiphoton luminescence background. Because of its sensitivity, isotropic environment, and straightforward experimental geometry, HRS optical activity constitutes a fundamental experimental breakthrough in chiral photonics for media including nanomaterials, metamaterials, and chemical molecules.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
A 32-channel multi-coil setup optimized for human brain shimming at 9.4T

Aghaeifar, A., Zhou, J., Heule, R., Tabibian, B., Schölkopf, B., Jia, F., Zaitsev, M., Scheffler, K.

Magnetic Resonance in Medicine, 2019, (Early View) (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl fig multidimensional contrast limited adaptive histogram equalization kb
Multidimensional Contrast Limited Adaptive Histogram Equalization

Stimper, V., Bauer, S., Ernstorfer, R., Schölkopf, B., Xian, R. P.

IEEE Access, 7, pages: 165437-165447, 2019 (article)

ei

arXiv link (url) DOI [BibTex]

arXiv link (url) DOI [BibTex]


no image
Enhancing Human Learning via Spaced Repetition Optimization

Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the National Academy of Sciences, 2019, PNAS published ahead of print January 22, 2019 (article)

ei

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


Thumb xl screenshot 2019 03 25 at 14.29.22
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots

Büchler, D., Calandra, R., Peters, J.

2019 (article) Submitted

Abstract
High-speed and high-acceleration movements are inherently hard to control. Applying learning to the control of such motions on anthropomorphic robot arms can improve the accuracy of the control but might damage the system. The inherent exploration of learning approaches can lead to instabilities and the robot reaching joint limits at high speeds. Having hardware that enables safe exploration of high-speed and high-acceleration movements is therefore desirable. To address this issue, we propose to use robots actuated by Pneumatic Artificial Muscles (PAMs). In this paper, we present a four degrees of freedom (DoFs) robot arm that reaches high joint angle accelerations of up to 28000 °/s^2 while avoiding dangerous joint limits thanks to the antagonistic actuation and limits on the air pressure ranges. With this robot arm, we are able to tune control parameters using Bayesian optimization directly on the hardware without additional safety considerations. The achieved tracking performance on a fast trajectory exceeds previous results on comparable PAM-driven robots. We also show that our system can be controlled well on slow trajectories with PID controllers due to careful construction considerations such as minimal bending of cables, lightweight kinematics and minimal contact between PAMs and PAMs with the links. Finally, we propose a novel technique to control the the co-contraction of antagonistic muscle pairs. Experimental results illustrate that choosing the optimal co-contraction level is vital to reach better tracking performance. Through the use of PAM-driven robots and learning, we do a small step towards the future development of robots capable of more human-like motions.

ei

Arxiv Video [BibTex]


no image
Inferring causation from time series with perspectives in Earth system sciences

Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M., van Nes, E., Peters, J., Quax, R., Reichstein, M., Scheffer, M. S. B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., Zscheischler, J.

Nature Communications, 2019 (article) In revision

ei

[BibTex]

[BibTex]


no image
Quantum mean embedding of probability distributions

Kübler, J. M., Muandet, K., Schölkopf, B.

Physical Review Research, 1(3):033159, American Physical Society, 2019 (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces

Klus, S., Schuster, I., Muandet, K.

Journal of Nonlinear Science, 2019, First Online: 21 August 2019 (article)

ei

DOI [BibTex]

DOI [BibTex]

2012


no image
Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices

Cherian, A., Sra, S., Banerjee, A., Papanikolopoulos, N.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2161-2174, December 2012 (article)

ei

DOI [BibTex]

2012


DOI [BibTex]


no image
Hippocampal-Cortical Interaction during Periods of Subcortical Silence

Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A.

Nature, 491, pages: 547-553, November 2012 (article)

Abstract
Hippocampal ripples, episodic high-frequency field-potential oscillations primarily occurring during sleep and calmness, have been described in mice, rats, rabbits, monkeys and humans, and so far they have been associated with retention of previously acquired awake experience. Although hippocampal ripples have been studied in detail using neurophysiological methods, the global effects of ripples on the entire brain remain elusive, primarily owing to a lack of methodologies permitting concurrent hippocampal recordings and whole-brain activity mapping. By combining electrophysiological recordings in hippocampus with ripple-triggered functional magnetic resonance imaging, here we show that most of the cerebral cortex is selectively activated during the ripples, whereas most diencephalic, midbrain and brainstem regions are strongly and consistently inhibited. Analysis of regional temporal response patterns indicates that thalamic activity suppression precedes the hippocampal population burst, which itself is temporally bounded by massive activations of association and primary cortical areas. These findings suggest that during off-line memory consolidation, synergistic thalamocortical activity may be orchestrating a privileged interaction state between hippocampus and cortex by silencing the output of subcortical centres involved in sensory processing or potentially mediating procedural learning. Such a mechanism would cause minimal interference, enabling consolidation of hippocampus-dependent memory.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Thermodynamic limits of dynamic cooling

Allahverdyan, A., Hovhannisyan, K., Janzing, D., Mahler, G.

Physical Review E, 84(4):16, October 2012 (article)

Abstract
We study dynamic cooling, where an externally driven two-level system is cooled via reservoir, a quantum system with initial canonical equilibrium state. We obtain explicitly the minimal possible temperature Tmin>0 reachable for the two-level system. The minimization goes over all unitary dynamic processes operating on the system and reservoir and over the reservoir energy spectrum. The minimal work needed to reach Tmin grows as 1/Tmin. This work cost can be significantly reduced, though, if one is satisfied by temperatures slightly above Tmin. Our results on Tmin>0 prove unattainability of the absolute zero temperature without ambiguities that surround its derivation from the entropic version of the third law. We also study cooling via a reservoir consisting of N≫1 identical spins. Here we show that Tmin∝1/N and find the maximal cooling compatible with the minimal work determined by the free energy. Finally we discuss cooling by reservoir with an initially microcanonic state and show that although a purely microcanonic state can yield the zero temperature, the unattainability is recovered when taking into account imperfections in preparing the microcanonic state.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
GLIDE: GPU-Based Linear Regression for Detection of Epistasis

Kam-Thong, T., Azencott, C., Cayton, L., Pütz, B., Altmann, A., Karbalai, N., Sämann, P., Schölkopf, B., Müller-Myhsok, B., Borgwardt, K.

Human Heredity, 73(4):220-236, September 2012 (article)

Abstract
Due to recent advances in genotyping technologies, mapping phenotypes to single loci in the genome has become a standard technique in statistical genetics. However, one-locus mapping fails to explain much of the phenotypic variance in complex traits. Here, we present GLIDE, which maps phenotypes to pairs of genetic loci and systematically searches for the epistatic interactions expected to reveal part of this missing heritability. GLIDE makes use of the computational power of consumer-grade graphics cards to detect such interactions via linear regression. This enabled us to conduct a systematic two-locus mapping study on seven disease data sets from the Wellcome Trust Case Control Consortium and on in-house hippocampal volume data in 6 h per data set, while current single CPU-based approaches require more than a year’s time to complete the same task.

ei

Web [BibTex]

Web [BibTex]


no image
Fast projection onto mixed-norm balls with applications

Sra, S.

Minining and Knowledge Discovery (DMKD), 25(2):358-377, September 2012 (article)

ei

DOI [BibTex]

DOI [BibTex]


no image
Bayesian estimation of free energies from equilibrium simulations

Habeck, M.

Physical Review Letters, 109(10):5, September 2012 (article)

Abstract
Free energy calculations are an important tool in statistical physics and biomolecular simulation. This Letter outlines a Bayesian method to estimate free energies from equilibrium Monte Carlo simulations. A Gibbs sampler is developed that allows efficient sampling of free energies and the density of states. The Gibbs sampling output can be used to estimate expected free energy differences and their uncertainties. The probabilistic formulation offers a unifying framework for existing methods such as the weighted histogram analysis method and the multistate Bennett acceptance ratio; both are shown to be approximate versions of the full probabilistic treatment.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
PAC-Bayesian Inequalities for Martingales

Seldin, Y., Laviolette, F., Cesa-Bianchi, N., Shawe-Taylor, J., Auer, P.

IEEE Transactions on Information Theory, 58(12):7086-7093, June 2012 (article)

Abstract
We present a set of high-probability inequalities that control the concentration of weighted averages of multiple (possibly uncountably many) simultaneously evolving and interdependent martingales. We also present a comparison inequality that bounds expectation of a convex function of martingale difference type variables by expectation of the same function of independent Bernoulli variables. This inequality is applied to derive a tighter analog of Hoeffding-Azuma inequality.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


Thumb xl screen shot 2017 09 21 at 00.54.33
Entropy Search for Information-Efficient Global Optimization

Hennig, P., Schuler, C.

Journal of Machine Learning Research, 13, pages: 1809-1837, -, June 2012 (article)

Abstract
Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum. The reason for the absence of probabilistic global optimizers is that the corresponding inference problem is intractable in several ways. This paper develops desiderata for probabilistic optimization algorithms, then presents a concrete algorithm which addresses each of the computational intractabilities with a sequence of approximations and explicitly adresses the decision problem of maximizing information gain from each evaluation.

ei pn

PDF Web Project Page [BibTex]

PDF Web Project Page [BibTex]


no image
A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

Nere, A., Olcese, U., Balduzzi, D., Tononi, G.

PLoS ONE, 7(5):17, May 2012 (article)

Abstract
In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

ei

PDF Web DOI [BibTex]


no image
Online Kernel-based Learning for Task-Space Tracking Robot Control

Nguyen-Tuong, D., Peters, J.

IEEE Transactions on Neural Networks and Learning Systems, 23(9):1417-1425, May 2012 (article)

Abstract
Abstract—Task-space control of redundant robot systems based on analytical models is known to be susceptive to modeling errors. Here, data driven model learning methods may present an interesting alternative approach. However, learning models for task-space tracking control from sampled data is an illposed problem. In particular, the same input data point can yield many different output values, which can form a non-convex solution space. Because the problem is ill-posed, models cannot be learned from such data using common regression methods. While learning of task-space control mappings is globally illposed, it has been shown in recent work that it is locally a well-defined problem. In this paper, we use this insight to formulate a local, kernel-based learning approach for online model learning for task-space tracking control. We propose a parametrization for the local model which makes an application in task-space tracking control of redundant robots possible. The model parametrization further allows us to apply the kerneltrick and, therefore, enables a formulation within the kernel learning framework. For evaluations, we show the ability of the method for online model learning for task-space tracking control of redundant robots.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


no image
Information-geometric approach to inferring causal directions

Janzing, D., Mooij, J., Zhang, K., Lemeire, J., Zscheischler, J., Daniušis, P., Steudel, B., Schölkopf, B.

Artificial Intelligence, 182-183, pages: 1-31, May 2012 (article)

Abstract
While conventional approaches to causal inference are mainly based on conditional (in)dependences, recent methods also account for the shape of (conditional) distributions. The idea is that the causal hypothesis “X causes Y” imposes that the marginal distribution PX and the conditional distribution PY|X represent independent mechanisms of nature. Recently it has been postulated that the shortest description of the joint distribution PX,Y should therefore be given by separate descriptions of PX and PY|X. Since description length in the sense of Kolmogorov complexity is uncomputable, practical implementations rely on other notions of independence. Here we define independence via orthogonality in information space. This way, we can explicitly describe the kind of dependence that occurs between PY and PX|Y making the causal hypothesis “Y causes X” implausible. Remarkably, this asymmetry between cause and effect becomes particularly simple if X and Y are deterministically related. We present an inference method that works in this case. We also discuss some theoretical results for the non-deterministic case although it is not clear how to employ them for a more general inference method.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Sparse regularized regression identifies behaviorally-relevant stimulus features from psychophysical data

Schönfelder, V., Wichmann, F.

Journal of the Acoustical Society of America, 131(5):3953-3969, May 2012 (article)

Abstract
As a prerequisite to quantitative psychophysical models of sensory processing it is necessary to learn to what extent decisions in behavioral tasks depend on specific stimulus features, the perceptual cues. Based on relative linear combination weights, this study demonstrates how stimulus-response data can be analyzed in this regard relying on an L1-regularized multiple logistic regression, a modern statistical procedure developed in machine learning. This method prevents complex models from over-fitting to noisy data. In addition, it enforces “sparse” solutions, a computational approximation to the postulate that a good model should contain the minimal set of predictors necessary to explain the data. In simulations, behavioral data from a classical auditory tone-in-noise detection task were generated. The proposed method is shown to precisely identify observer cues from a large set of covarying, interdependent stimulus features—a setting where standard correlational and regression methods fail. The proposed method succeeds for a wide range of signal-to-noise ratios and for deterministic as well as probabilistic observers. Furthermore, the detailed decision rules of the simulated observers were reconstructed from the estimated linear model weights allowing predictions of responses on the basis of individual stimuli.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
glm-ie: The Generalised Linear Models Inference and Estimation Toolbox

Nickisch, H.

Journal of Machine Learning Research, 13, pages: 1699-1703, May 2012 (article)

Abstract
The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some The code is fully compatible to both Matlab 7.x and GNU Octave 3.3.x. Abstract Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework.

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


no image
Feature Selection via Dependence Maximization

Song, L., Smola, A., Gretton, A., Bedo, J., Borgwardt, K.

Journal of Machine Learning Research, 13, pages: 1393-1434, May 2012 (article)

Abstract
We introduce a framework of feature selection based on dependence maximization between the selected features and the labels of an estimation problem, using the Hilbert-Schmidt Independence Criterion. The key idea is that good features should be highly dependent on the labels. Our approach leads to a greedy procedure for feature selection. We show that a number of existing feature selectors are special cases of this framework. Experiments on both artificial and real-world data show that our feature selector works well in practice.

ei

PDF [BibTex]

PDF [BibTex]


no image
High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces

Grosse-Wentrup, M., Schölkopf, B.

Journal of Neural Engineering, 9(4):046001, May 2012 (article)

Abstract
Subjects operating a brain–computer interface (BCI) based on sensorimotor rhythms exhibit large variations in performance over the course of an experimental session. Here, we show that high-frequency γ-oscillations, originating in fronto-parietal networks, predict such variations on a trial-to-trial basis. We interpret this finding as empirical support for an influence of attentional networks on BCI performance via modulation of the sensorimotor rhythm.

ei

Web DOI [BibTex]


no image
ShapePheno: Unsupervised extraction of shape phenotypes from biological image collections

Karaletsos, T., Stegle, O., Dreyer, C., Winn, J., Borgwardt, K.

Bioinformatics, 28(7):1001-1008, April 2012 (article)

Abstract
Motivation: Accurate large-scale phenotyping has recently gained considerable importance in biology. For example, in genome wide association studies technological advances have rendered genotyping cheap, leaving phenotype acquisition as the major bottleneck. Automatic image analysis is one major strategy to phenotype individuals in large numbers. Current approaches for visual phenotyping focus predominantly on summarizing statistics and geometric measures, such as height and width of an individual, or color histograms and patterns. However, more subtle, but biologically informative phenotypes, such as the local deformation of the shape of an individual with respect to the population mean cannot be automatically extracted and quantified by current techniques. Results: We propose a probabilistic machine learning model that allows for the extraction of deformation phenotypes from biological images, making them available as quantitative traits for downstream analysis. Our approach jointly models a collection of images using a learned common template that is mapped onto each image through a deformable smooth transformation. In a case study we analyze the shape deformations of 388 guppy fish (Poecilia reticulata). We find that the flexible shape phenotypes our model extracts are complementary to basic geometric measures. Moreover, these quantitative traits assort the observations into distinct groups and can be mapped to polymorphic genetic loci of the sample set.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
A New Perceptual Bias Reveals Suboptimal Population Decoding of Sensory Responses

Putzeys, T., Bethge, M., Wichmann, F., Wagemans, J., Goris, R.

PLoS Computational Biology, 8(4):1-13, April 2012 (article)

Abstract
Several studies have reported optimal population decoding of sensory responses in two-alternative visual discrimination tasks. Such decoding involves integrating noisy neural responses into a more reliable representation of the likelihood that the stimuli under consideration evoked the observed responses. Importantly, an ideal observer must be able to evaluate likelihood with high precision and only consider the likelihood of the two relevant stimuli involved in the discrimination task. We report a new perceptual bias suggesting that observers read out the likelihood representation with remarkably low precision when discriminating grating spatial frequencies. Using spectrally filtered noise, we induced an asymmetry in the likelihood function of spatial frequency. This manipulation mainly affects the likelihood of spatial frequencies that are irrelevant to the task at hand. Nevertheless, we find a significant shift in perceived grating frequency, indicating that observers evaluate likelihoods of a broad range of irrelevant frequencies and discard prior knowledge of stimulus alternatives when performing two-alternative discrimination.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Patterns of cis regulatory variation in diverse human populations

Stranger, BE., Montgomery, SB., Dimas, AS., Parts, L., Stegle, O., Ingle, CE., Sekowska, M., Smith, GD., Evans, D., Gutierrez-Arcelus, M., others

PLoS genetics, 8(4):e1002639, April 2012 (article)

Abstract
he genetic basis of gene expression variation has long been studied with the aim to understand the landscape of regulatory variants, but also more recently to assist in the interpretation and elucidation of disease signals. To date, many studies have looked in specific tissues and population-based samples, but there has been limited assessment of the degree of inter-population variability in regulatory variation. We analyzed genome-wide gene expression in lymphoblastoid cell lines from a total of 726 individuals from 8 global populations from the HapMap3 project and correlated gene expression levels with HapMap3 SNPs located in cis to the genes. We describe the influence of ancestry on gene expression levels within and between these diverse human populations and uncover a non-negligible impact on global patterns of gene expression. We further dissect the specific functional pathways differentiated between populations. We also identify 5,691 expression quantitative trait loci (eQTLs) after controlling for both non-genetic factors and population admixture and observe that half of the cis-eQTLs are replicated in one or more of the populations. We highlight patterns of eQTL-sharing between populations, which are partially determined by population genetic relatedness, and discover significant sharing of eQTL effects between Asians, European-admixed, and African subpopulations. Specifically, we observe that both the effect size and the direction of effect for eQTLs are highly conserved across populations. We observe an increasing proximity of eQTLs toward the transcription start site as sharing of eQTLs among populations increases, highlighting that variants close to TSS have stronger effects and therefore are more likely to be detected across a wider panel of populations. Together these results offer a unique picture and resource of the degree of differentiation among human populations in functional regulatory variation and provide an estimate for the transferability of complex trait variants across populations.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
A Kernel Two-Sample Test

Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.

Journal of Machine Learning Research, 13, pages: 723-773, March 2012 (article)

Abstract
We propose a framework for analyzing and comparing distributions, which we use to construct statistical tests to determine if two samples are drawn from different distributions. Our test statistic is the largest difference in expectations over functions in the unit ball of a reproducing kernel Hilbert space (RKHS), and is called the maximum mean discrepancy (MMD). We present two distribution-free tests based on large deviation bounds for the MMD, and a third test based on the asymptotic distribution of this statistic. The MMD can be computed in quadratic time, although efficient linear time approximations are available. Our statistic is an instance of an integral probability metric, and various classical metrics on distributions are obtained when alternative function classes are used in place of an RKHS. We apply our two-sample tests to a variety of problems, including attribute matching for databases using the Hungarian marriage method, where they perform strongly. Excellent performance is also obtained when comparing distributions over graphs, for which these are the first such tests.

ei

PDF Web [BibTex]

PDF Web [BibTex]


no image
Technical performance evaluation of a human brain PET/MRI system

Kolb, A., Wehrl, H., Hofmann, M., Judenhofer, M., Eriksson, L., Ladebeck, R., Lichy, M., Byars, L., Michel, C., Schlemmer, H., Schmand, M., Claussen, C., Sossi, V., Pichler, B.

European Radiology, 22(8):1776-1788, March 2012 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components

Lampert, C., Peters, J.

Journal of Real-Time Image Processing, 7(1):31-41, March 2012 (article)

Abstract
We describe RTblob, a high speed vision system that detects objects in cluttered scenes based on their color and shape at a speed of over 800 frames/s. Because the system is available as open-source software and relies only on off-the-shelf PC hardware components, it can provide the basis for multiple application scenarios. As an illustrative example, we show how RTblob can be used in a robotic table tennis scenario to estimate ball trajectories through 3D space simultaneously from four cameras images at a speed of 200 Hz.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


no image
A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of Is(x)

Sra, S.

Computational Statistics, 27(1):177-190, March 2012 (article)

Abstract
In high-dimensional directional statistics one of the most basic probability distributions is the von Mises-Fisher (vMF) distribution. Maximum likelihood estimation for the vMF distribution turns out to be surprisingly hard because of a difficult transcendental equation that needs to be solved for computing the concentration parameter κ. This paper is a followup to the recent paper of Tanabe et al. (Comput Stat 22(1):145–157, 2007), who exploited inequalities about Bessel function ratios to obtain an interval in which the parameter estimate for κ should lie; their observation lends theoretical validity to the heuristic approximation of Banerjee et al. (JMLR 6:1345–1382, 2005). Tanabe et al. (Comput Stat 22(1):145–157, 2007) also presented a fixed-point algorithm for computing improved approximations for κ. However, their approximations require (potentially significant) additional computation, and in this short paper we show that given the same amount of computation as their method, one can achieve more accurate approximations using a truncated Newton method. A more interesting contribution of this paper is a simple algorithm for computing I s (x): the modified Bessel function of the first kind. Surprisingly, our naïve implementation turns out to be several orders of magnitude faster for large arguments common to high-dimensional data, than the standard implementations in well-established software such as Mathematica ©, Maple ©, and Gp/Pari.

ei

PDF PDF DOI [BibTex]


no image
An online brain–computer interface based on shifting attention to concurrent streams of auditory stimuli

Hill, N., Schölkopf, B.

Journal of Neural Engineering, 9(2):026011, February 2012 (article)

Abstract
We report on the development and online testing of an electroencephalogram-based brain–computer interface (BCI) that aims to be usable by completely paralysed users—for whom visual or motor-system-based BCIs may not be suitable, and among whom reports of successful BCI use have so far been very rare. The current approach exploits covert shifts of attention to auditory stimuli in a dichotic-listening stimulus design. To compare the efficacy of event-related potentials (ERPs) and steady-state auditory evoked potentials (SSAEPs), the stimuli were designed such that they elicited both ERPs and SSAEPs simultaneously. Trial-by-trial feedback was provided online, based on subjects' modulation of N1 and P3 ERP components measured during single 5 s stimulation intervals. All 13 healthy subjects were able to use the BCI, with performance in a binary left/right choice task ranging from 75% to 96% correct across subjects (mean 85%). BCI classification was based on the contrast between stimuli in the attended stream and stimuli in the unattended stream, making use of every stimulus, rather than contrasting frequent standard and rare 'oddball' stimuli. SSAEPs were assessed offline: for all subjects, spectral components at the two exactly known modulation frequencies allowed discrimination of pre-stimulus from stimulus intervals, and of left-only stimuli from right-only stimuli when one side of the dichotic stimulus pair was muted. However, attention modulation of SSAEPs was not sufficient for single-trial BCI communication, even when the subject's attention was clearly focused well enough to allow classification of the same trials via ERPs. ERPs clearly provided a superior basis for BCI. The ERP results are a promising step towards the development of a simple-to-use, reliable yes/no communication system for users in the most severely paralysed states, as well as potential attention-monitoring and -training applications outside the context of assistive technology.

ei

PDF DOI [BibTex]


no image
A non-monotonic method for large-scale non-negative least squares

Kim, D., Sra, S., Dhillon, I. S.

Optimization Methods and Software, 28(5):1012-1039, Febuary 2012 (article)

ei

DOI [BibTex]

DOI [BibTex]