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2013


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A neural population model for visual pattern detection

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

Psychological Review, 120(3):472–496, 2013 (article)

DOI [BibTex]

2013

DOI [BibTex]


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Accurate indel prediction using paired-end short reads

Grimm, D., Hagmann, J., Koenig, D., Weigel, D., Borgwardt, KM.

BMC Genomics, 14(132), 2013 (article)

Web DOI [BibTex]

Web DOI [BibTex]


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Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising

Bottou, L., Peters, J., Quiñonero-Candela, J., Charles, D., Chickering, D., Portugualy, E., Ray, D., Simard, P., Snelson, E.

Journal of Machine Learning Research, 14, pages: 3207-3260, 2013 (article)

Web link (url) [BibTex]

Web link (url) [BibTex]


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When luminance increment thresholds depend on apparent lightness

Maertens, M., Wichmann, F.

Journal of Vision, 13(6):1-11, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Efficient network-guided multi-locus association mapping with graph cuts

Azencott, C., Grimm, D., Sugiyama, M., Kawahara, Y., Borgwardt, K.

Bioinformatics, 29(13):i171-i179, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Quantifying causal influences

Janzing, D., Balduzzi, D., Grosse-Wentrup, M., Schölkopf, B.

Annals of Statistics, 41(5):2324-2358, 2013 (article)

Web [BibTex]

Web [BibTex]


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Probabilistic movement modeling for intention inference in human-robot interaction

Wang, Z., Mülling, K., Deisenroth, M., Ben Amor, H., Vogt, D., Schölkopf, B., Peters, J.

International Journal of Robotics Research, 32(7):841-858, 2013 (article)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Blind Retrospective Motion Correction of MR Images

Loktyushin, A., Nickisch, H., Pohmann, R., Schölkopf, B.

Magnetic Resonance in Medicine (MRM), 70(6):1608–1618, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Modeling fixation locations using spatial point processes

Barthelmé, S., Trukenbrod, H., Engbert, R., Wichmann, F.

Journal of Vision, 13(12):1-34, 2013 (article)

Abstract
Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.

Web DOI [BibTex]

Web DOI [BibTex]


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A probabilistic model for secondary structure prediction from protein chemical shifts

Mechelke, M., Habeck, M.

Proteins: Structure, Function, and Bioinformatics, 81(6):984–993, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Climate Extremes and the Carbon Cycle

Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M., Seneviratne, S., Zscheischler, J., Beer, C., Buchmann, N., Frank, D., Papale, D., Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A., Wattenbach, M.

Nature, 500, pages: 287-295, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Identification of stimulus cues in narrow-band tone-in-noise detection using sparse observer models

Schönfelder, V., Wichmann, F.

Journal of the Acoustical Society of America, 134(1):447-463, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Probabilistic Model-based Imitation Learning

Englert, P., Paraschos, A., Peters, J., Deisenroth, M.

Adaptive Behavior Journal, 21(5):388-403, 2013 (article)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Metabolic cost as an organizing principle for cooperative learning

Balduzzi, D., Ortega, P., Besserve, M.

Advances in Complex Systems, 16(02n03):1350012, 2013 (article)

Web DOI [BibTex]

Web DOI [BibTex]


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MR-based PET Attenuation Correction for PET/MR Imaging

Bezrukov, I., Mantlik, F., Schmidt, H., Schölkopf, B., Pichler, B.

Seminars in Nuclear Medicine, 43(1):45-59, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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MR-based Attenuation Correction Methods for Improved PET Quantification in Lesions within Bone and Susceptibility Artifact Regions

Bezrukov, I., Schmidt, H., Mantlik, F., Schwenzer, N., Brendle, C., Schölkopf, B., Pichler, B.

Journal of Nuclear Medicine, 54(10):1768-1774, 2013 (article)

Abstract
Hybrid PET/MR systems have recently entered clinical practice. Thus, the accuracy of MR-based attenuation correction in simultaneously acquired data can now be investigated. We assessed the accuracy of 4 methods of MR-based attenuation correction in lesions within soft tissue, bone, and MR susceptibility artifacts: 2 segmentation-based methods (SEG1, provided by the manufacturer, and SEG2, a method with atlas-based susceptibility artifact correction); an atlas- and pattern recognition–based method (AT&PR), which also used artifact correction; and a new method combining AT&PR and SEG2 (SEG2wBONE). Methods: Attenuation maps were calculated for the PET/MR datasets of 10 patients acquired on a whole-body PET/MR system, allowing for simultaneous acquisition of PET and MR data. Eighty percent iso-contour volumes of interest were placed on lesions in soft tissue (n = 21), in bone (n = 20), near bone (n = 19), and within or near MR susceptibility artifacts (n = 9). Relative mean volume-of-interest differences were calculated with CT-based attenuation correction as a reference. Results: For soft-tissue lesions, none of the methods revealed a significant difference in PET standardized uptake value relative to CT-based attenuation correction (SEG1, −2.6% ± 5.8%; SEG2, −1.6% ± 4.9%; AT&PR, −4.7% ± 6.5%; SEG2wBONE, 0.2% ± 5.3%). For bone lesions, underestimation of PET standardized uptake values was found for all methods, with minimized error for the atlas-based approaches (SEG1, −16.1% ± 9.7%; SEG2, −11.0% ± 6.7%; AT&PR, −6.6% ± 5.0%; SEG2wBONE, −4.7% ± 4.4%). For lesions near bone, underestimations of lower magnitude were observed (SEG1, −12.0% ± 7.4%; SEG2, −9.2% ± 6.5%; AT&PR, −4.6% ± 7.8%; SEG2wBONE, −4.2% ± 6.2%). For lesions affected by MR susceptibility artifacts, quantification errors could be reduced using the atlas-based artifact correction (SEG1, −54.0% ± 38.4%; SEG2, −15.0% ± 12.2%; AT&PR, −4.1% ± 11.2%; SEG2wBONE, 0.6% ± 11.1%). Conclusion: For soft-tissue lesions, none of the evaluated methods showed statistically significant errors. For bone lesions, significant underestimations of −16% and −11% occurred for methods in which bone tissue was ignored (SEG1 and SEG2). In the present attenuation correction schemes, uncorrected MR susceptibility artifacts typically result in reduced attenuation values, potentially leading to highly reduced PET standardized uptake values, rendering lesions indistinguishable from background. While AT&PR and SEG2wBONE show accurate results in both soft tissue and bone, SEG2wBONE uses a two-step approach for tissue classification, which increases the robustness of prediction and can be applied retrospectively if more precision in bone areas is needed.

Web DOI [BibTex]

Web DOI [BibTex]


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Learning output kernels for multi-task problems

Dinuzzo, F.

Neurocomputing, 118, pages: 119-126, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Analytical probabilistic modeling for radiation therapy treatment planning

Bangert, M., Hennig, P., Oelfke, U.

Physics in Medicine and Biology, 58(16):5401-5419, 2013 (article)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Imaging Findings and Therapy Response Monitoring in Chronic Sclerodermatous Graft-Versus-Host Disease: Preliminary Data of a Simultaneous PET/MRI Approach

Sauter, A., Schmidt, H., Mantlik, F., Kolb, A., Federmann, B., Pfannenberg, C., Reimold, M., Pichler, B., Bethge, W., Horger, M.

Clinical Nuclear Medicine, 38(8):e309-e317, 2013 (article)

Abstract
PURPOSE: Our objective was a multifunctional imaging approach of chronic sclerodermatous graft-versus-host disease (ScGVHD) and its course during therapy using PET/MRI. METHODS: We performed partial-body PET/CT and PET/MRI of the calf in 6 consecutively recruited patients presenting with severe ScGVHD. The patients were treated with different immunosuppressive regimens and supportive therapies. PET/CT scanning started 60.5 +/- 3.3 minutes, PET/MRI imaging 139.5 +/- 16.7 minutes after F-FDG application. MRI acquisition included T1- (precontrast and postcontrast) and T2-weighted sequences. SUVmean, T1 contrast enhancement, and T2 signal intensity from region-of-interest analysis were calculated for different fascial and muscular compartments. In addition, musculoskeletal MRI findings and the modified Rodnan skin score were assessed. All patients underwent imaging follow-up. RESULTS: At baseline PET/MRI, ScGVHD-related musculoskeletal abnormalities consisted of increased signal and/or thickening of involved anatomical structures on T2-weighted and T1 postcontrast images as well as an increased FDG uptake. At follow-up, ScGVHD-related imaging findings decreased (SUVmean n = 4, mean T1 contrast enhancement n = 5, mean T2 signal intensity n = 3) or progressed (SUVmean n = 3, mean T1 contrast enhancement n = 2, mean T2 signal intensity n = 4). Clinically modified Rodnan skin score improved for 5 follow-ups and progressed for 2. SUVmean values correlated between PET/CT and PET/MRI acquisition (r = 0.660, P = 0.014), T1 contrast enhancement, and T2 signal (r = 0.668, P = 0.012), but not between the SUVmean values and the MRI parameters. CONCLUSIONS: PET/MRI as a combined morphological and functional technique seems to assess the inflammatory processes from different points of view and provides therefore in part complementary information

Web [BibTex]

Web [BibTex]


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A Survey on Policy Search for Robotics, Foundations and Trends in Robotics

Deisenroth, M., Neumann, G., Peters, J.

Foundations and Trends in Robotics, 2(1-2):1-142, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Reinforcement Learning in Robotics: A Review

Kober, J., Bagnell, D., Peters, J.

International Journal of Robotics Research, 32(11):1238–1274, 2013 (article)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Multimodal information improves the rapid detection of mental fatigue

Laurent, F., Valderrama, M., Besserve, M., Guillard, M., Lachaux, J., Martinerie, J., Florence, G.

Biomedical Signal Processing and Control, 8(4):400 - 408, 2013 (article)

Web DOI [BibTex]

Web DOI [BibTex]


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Interactive Domain Adaptation for the Classification of Remote Sensing Images using Active Learning

Persello, C.

IEEE Geoscience and Remote Sensing Letters, 10(4):736-740, 2013 (article)

DOI [BibTex]


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Learning to Select and Generalize Striking Movements in Robot Table Tennis

Mülling, K., Kober, J., Kroemer, O., Peters, J.

International Journal of Robotics Research, 32(3):263-279, 2013 (article)

PDF DOI [BibTex]


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HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization

Schultz, T., Schlaffke, L., Schölkopf, B., Schmidt-Wilcke, T.

Computer Graphics Forum, 32(3):121-130, (Editors: B Preim, P Rheingans, and H Theisel), Blackwell Publishing, Oxford, UK, Eurographics Conference on Visualization (EuroVis), 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Detection and attribution of large spatiotemporal extreme events in Earth observation data

Zscheischler, J., Mahecha, M., Harmeling, S., Reichstein, M.

Ecological Informatics, 15, pages: 66-73, 2013 (article)

Abstract
Latest climate projections suggest that both frequency and intensity of climate extremes will be substantially modified over the course of the coming decades. As a consequence, we need to understand to what extent and via which pathways climate extremes affect the state and functionality of terrestrial ecosystems and the associated biogeochemical cycles on a global scale. So far the impacts of climate extremes on the terrestrial biosphere were mainly investigated on the basis of case studies, while global assessments are widely lacking. In order to facilitate global analysis of this kind, we present a methodological framework that firstly detects spatiotemporally contiguous extremes in Earth observations, and secondly infers the likely pathway of the preceding climate anomaly. The approach does not require long time series, is computationally fast, and easily applicable to a variety of data sets with different spatial and temporal resolutions. The key element of our analysis strategy is to directly search in the relevant observations for spatiotemporally connected components exceeding a certain percentile threshold. We also put an emphasis on characterization of extreme event distribution, and scrutinize the attribution issue. We exemplify the analysis strategy by exploring the fraction of absorbed photosynthetically active radiation (fAPAR) from 1982 to 2011. Our results suggest that the hot spots of extremes in fAPAR lie in Northeastern Brazil, Southeastern Australia, Kenya and Tanzania. Moreover, we demonstrate that the size distribution of extremes follow a distinct power law. The attribution framework reveals that extremes in fAPAR are primarily driven by phases of water scarcity.

Web DOI [BibTex]

Web DOI [BibTex]


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Simultaneous PET/MR reveals Brain Function in Activated and Resting State on Metabolic, Hemodynamic and Multiple Temporal Scales

Wehrl, H., Hossain, M., Lankes, K., Liu, C., Bezrukov, I., Martirosian, P., Schick, F., Reischl, G., Pichler, B.

Nature Medicine, 19, pages: 1184–1189, 2013 (article)

Abstract
Combined positron emission tomography (PET) and magnetic resonance imaging (MRI) is a new tool to study functional processes in the brain. Here we study brain function in response to a barrel-field stimulus simultaneously using PET, which traces changes in glucose metabolism on a slow time scale, and functional MRI (fMRI), which assesses fast vascular and oxygenation changes during activation. We found spatial and quantitative discrepancies between the PET and the fMRI activation data. The functional connectivity of the rat brain was assessed by both modalities: the fMRI approach determined a total of nine known neural networks, whereas the PET method identified seven glucose metabolism–related networks. These results demonstrate the feasibility of combined PET-MRI for the simultaneous study of the brain at activation and rest, revealing comprehensive and complementary information to further decode brain function and brain networks.

Web DOI [BibTex]

Web DOI [BibTex]


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Finding Potential Support Vectors in Separable Classification Problems

Varagnolo, D., Del Favero, S., Dinuzzo, F., Schenato, L., Pillonetto, G.

IEEE Transactions on Neural Networks and Learning Systems, 24(11):1799-1813, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Open-Box Spectral Clustering: Applications to Medical Image Analysis

Schultz, T., Kindlmann, G.

IEEE Transactions on Visualization and Computer Graphics, 19(12):2100-2108, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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im3shape: a maximum likelihood galaxy shear measurement code for cosmic gravitational lensing

Zuntz, J., Kacprzak, T., Voigt, L., Hirsch, M., Rowe, B., Bridle, S.

Monthly Notices of the Royal Astronomical Society, 434(2):1604-1618, Oxford University Press, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Accurate detection of differential RNA processing

Drewe, P., Stegle, O., Hartmann, L., Kahles, A., Bohnert, R., Wachter, A., Borgwardt, K. M., Rätsch, G.

Nucleic Acids Research, 41(10):5189-5198, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Detecting regulatory gene–environment interactions with unmeasured environmental factors

Fusi, N., Lippert, C., Borgwardt, K. M., Lawrence, N. D., Stegle, O.

Bioinformatics, 29(11):1382-1389, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Fragmentation of Slow Wave Sleep after Onset of Complete Locked-In State

Soekadar, S. R., Born, J., Birbaumer, N., Bensch, M., Halder, S., Murguialday, A. R., Gharabaghi, A., Nijboer, F., Schölkopf, B., Martens, S.

Journal of Clinical Sleep Medicine, 9(9):951-953, 2013 (article)

DOI [BibTex]

DOI [BibTex]


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Structural learning

Braun, D

Scholarpedia, 8(10):12312, October 2013 (article)

Abstract
Structural learning in motor control refers to a metalearning process whereby an agent extracts (abstract) invariants from its sensorimotor stream when experiencing a range of environments that share similar structure. Such invariants can then be exploited for faster generalization and learning-to-learn when experiencing novel, but related task environments.

DOI [BibTex]

DOI [BibTex]


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The effect of model uncertainty on cooperation in sensorimotor interactions

Grau-Moya, J, Hez, E, Pezzulo, G, Braun, DA

Journal of the Royal Society Interface, 10(87):1-11, October 2013 (article)

Abstract
Decision-makers have been shown to rely on probabilistic models for perception and action. However, these models can be incorrect or partially wrong in which case the decision-maker has to cope with model uncertainty. Model uncertainty has recently also been shown to be an important determinant of sensorimotor behaviour in humans that can lead to risk-sensitive deviations from Bayes optimal behaviour towards worst-case or best-case outcomes. Here, we investigate the effect of model uncertainty on cooperation in sensorimotor interactions similar to the stag-hunt game, where players develop models about the other player and decide between a pay-off-dominant cooperative solution and a risk-dominant, non-cooperative solution. In simulations, we show that players who allow for optimistic deviations from their opponent model are much more likely to converge to cooperative outcomes. We also implemented this agent model in a virtual reality environment, and let human subjects play against a virtual player. In this game, subjects' pay-offs were experienced as forces opposing their movements. During the experiment, we manipulated the risk sensitivity of the computer player and observed human responses. We found not only that humans adaptively changed their level of cooperation depending on the risk sensitivity of the computer player but also that their initial play exhibited characteristic risk-sensitive biases. Our results suggest that model uncertainty is an important determinant of cooperation in two-player sensorimotor interactions.

DOI [BibTex]

DOI [BibTex]


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Thermodynamics as a theory of decision-making with information-processing costs

Ortega, PA, Braun, DA

Proceedings of the Royal Society of London A, 469(2153):1-18, May 2013 (article)

Abstract
Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here, we propose a thermodynamically inspired formalization of bounded rational decision-making where information processing is modelled as state changes in thermodynamic systems that can be quantified by differences in free energy. By optimizing a free energy, bounded rational decision-makers trade off expected utility gains and information-processing costs measured by the relative entropy. As a result, the bounded rational decision-making problem can be rephrased in terms of well-known variational principles from statistical physics. In the limit when computational costs are ignored, the maximum expected utility principle is recovered. We discuss links to existing decision-making frameworks and applications to human decision-making experiments that are at odds with expected utility theory. Since most of the mathematical machinery can be borrowed from statistical physics, the main contribution is to re-interpret the formalism of thermodynamic free-energy differences in terms of bounded rational decision-making and to discuss its relationship to human decision-making experiments.

DOI [BibTex]

DOI [BibTex]

2008


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Modelling contrast discrimination data suggest both the pedestal effect and stochastic resonance to be caused by the same mechanism

Goris, R., Wagemans, J., Wichmann, F.

Journal of Vision, 8(15):1-21, November 2008 (article)

Abstract
Computational models of spatial vision typically make use of a (rectified) linear filter, a nonlinearity and dominant late noise to account for human contrast discrimination data. Linear–nonlinear cascade models predict an improvement in observers' contrast detection performance when low, subthreshold levels of external noise are added (i.e., stochastic resonance). Here, we address the issue whether a single contrast gain-control model of early spatial vision can account for both the pedestal effect, i.e., the improved detectability of a grating in the presence of a low-contrast masking grating, and stochastic resonance. We measured contrast discrimination performance without noise and in both weak and moderate levels of noise. Making use of a full quantitative description of our data with few parameters combined with comprehensive model selection assessments, we show the pedestal effect to be more reduced in the presence of weak noise than in moderate noise. This reduction rules out independent, additive sources of performance improvement and, together with a simulation study, supports the parsimonious explanation that a single mechanism underlies the pedestal effect and stochastic resonance in contrast perception.

Web DOI [BibTex]


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The Effect of Mutual Information on Independent Component Analysis in EEG/MEG Analysis: A Simulation Study

Neumann, A., Grosse-Wentrup, M., Buss, M., Gramann, K.

International Journal of Neuroscience, 118(11):1534-1546, November 2008 (article)

Abstract
Objective: This study investigated the influence of mutual information (MI) on temporal and dipole reconstruction based on independent components (ICs) derived from independent component analysis (ICA). Method: Artificial electroencephalogram (EEG) datasets were created by means of a neural mass model simulating cortical activity of two neural sources within a four-shell spherical head model. Mutual information between neural sources was systematicallyvaried. Results: Increasing spatial error for reconstructed locations of ICs with increasing MI was observed. By contrast, the reconstruction error for the time course of source activity was largely independent of MI but varied systematically with Gaussianity of the sources. Conclusion: Independent component analysis is a viable tool for analyzing the temporal activity of EEG/MEG (magnetoencephalography) sources even if the underlying neural sources are mutually dependent. However, if ICA is used as a preprocessing algorithm for source localization, mutual information between sources introduces a bias in the reconstructed locations of the sources. Significance: Studies using ICA-algorithms based on MI have to be aware of possible errors in the spatial reconstruction of sources if these are coupled with other neural sources.

Web DOI [BibTex]

Web DOI [BibTex]


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gBoost: A Mathematical Programming Approach to Graph Classification and Regression

Saigo, H., Nowozin, S., Kadowaki, T., Kudo, T., Tsuda, K.

Machine Learning, 75(1):69-89, November 2008 (article)

Abstract
Graph mining methods enumerate frequently appearing subgraph patterns, which can be used as features for subsequent classification or regression. However, frequent patterns are not necessarily informative for the given learning problem. We propose a mathematical programming boosting method (gBoost) that progressively collects informative patterns. Compared to AdaBoost, gBoost can build the prediction rule with fewer iterations. To apply the boosting method to graph data, a branch-and-bound pattern search algorithm is developed based on the DFS code tree. The constructed search space is reused in later iterations to minimize the computation time. Our method can learn more efficiently than the simpler method based on frequent substructure mining, because the output labels are used as an extra information source for pruning the search space. Furthermore, by engineering the mathematical program, a wide range of machine learning problems can be solved without modifying the pattern search algorithm.

PDF DOI [BibTex]

PDF DOI [BibTex]


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Machine Learning for Motor Skills in Robotics

Peters, J.

K{\"u}nstliche Intelligenz, 2008(4):41-43, November 2008 (article)

Abstract
Autonomous robots that can adapt to novel situations has been a long standing vision of robotics, artificial intelligence, and the cognitive sciences. Early approaches to this goal during the heydays of artificial intelligence research in the late 1980s, however, made it clear that an approach purely based on reasoning or human insights would not be able to model all the perceptuomotor tasks of future robots. Instead, new hope was put in the growing wake of machine learning that promised fully adaptive control algorithms which learn both by observation and trial-and-error. However, to date, learning techniques have yet to fulfill this promise as only few methods manage to scale into the high-dimensional domains of manipulator and humanoid robotics and usually scaling was only achieved in precisely pre-structured domains. We have investigated the ingredients for a general approach to motor skill learning in order to get one step closer towards human-like performance. For doing so, we study two major components for such an approach, i.e., firstly, a theoretically well-founded general approach to representing the required control structures for task representation and execution and, secondly, appropriate learning algorithms which can be applied in this setting.

PDF Web [BibTex]

PDF Web [BibTex]


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Kernels, Regularization and Differential Equations

Steinke, F., Schölkopf, B.

Pattern Recognition, 41(11):3271-3286, November 2008 (article)

Abstract
Many common machine learning methods such as Support Vector Machines or Gaussian process inference make use of positive definite kernels, reproducing kernel Hilbert spaces, Gaussian processes, and regularization operators. In this work these objects are presented in a general, unifying framework, and interrelations are highlighted. With this in mind we then show how linear stochastic differential equation models can be incorporated naturally into the kernel framework. And vice versa, many kernel machines can be interpreted in terms of differential equations. We focus especially on ordinary differential equations, also known as dynamical systems, and it is shown that standard kernel inference algorithms are equivalent to Kalman filter methods based on such models. In order not to cloud qualitative insights with heavy mathematical machinery, we restrict ourselves to finite domains, implying that differential equations are treated via their corresponding finite difference equations.

PDF DOI [BibTex]

PDF DOI [BibTex]


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The genome of the simian and human malaria parasite Plasmodium knowlesi

Pain, A., Böhme, U., Berry, A., Mungall, K., Finn, R., Jackson, A., Mourier, T., Mistry, J., Pasini, E., Aslett, M., Balasubrammaniam, S., Borgwardt, K., Brooks, K., Carret, C., Carver, T., Cherevach, I., Chillingworth, T., Clarke, T., Galinski, M., Hall, N., Harper, D., Harris, D., Hauser, H., Ivens, A., Janssen, C., Keane, T., Larke, N., Lapp, S., Marti, M., Moule, S., Meyer, I., Ormond, D., Peters, N., Sanders, M., Sanders, T., Sergeant, T., Simmonds, M., Smith, F., Squares, R., Thurston, S., Tivey, A., Walker, D., White, B., Zuiderwijk, E., Churcher, C., Quail, M., Cowman, A., Turner, C., Rajandream, M., Kocken, C., Thomas, A., Newbold, C., Barrell, B., Berriman, M.

Nature, 455(7214):799-803, October 2008 (article)

Abstract
Plasmodium knowlesi is an intracellular malaria parasite whose natural vertebrate host is Macaca fascicularis (the 'kra' monkey); however, it is now increasingly recognized as a significant cause of human malaria, particularly in southeast Asia1, 2. Plasmodium knowlesi was the first malaria parasite species in which antigenic variation was demonstrated3, and it has a close phylogenetic relationship to Plasmodium vivax 4, the second most important species of human malaria parasite (reviewed in ref. 4). Despite their relatedness, there are important phenotypic differences between them, such as host blood cell preference, absence of a dormant liver stage or 'hypnozoite' in P. knowlesi, and length of the asexual cycle (reviewed in ref. 4). Here we present an analysis of the P. knowlesi (H strain, Pk1(A+) clone5) nuclear genome sequence. This is the first monkey malaria parasite genome to be described, and it provides an opportunity for comparison with the recently completed P. vivax genome4 and other sequenced Plasmodium genomes6, 7, 8. In contrast to other Plasmodium genomes, putative variant antigen families are dispersed throughout the genome and are associated with intrachromosomal telomere repeats. One of these families, the KIRs9, contains sequences that collectively match over one-half of the host CD99 extracellular domain, which may represent an unusual form of molecular mimicry.

PDF DOI [BibTex]

PDF DOI [BibTex]


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A BOLD window into brain waves

Balduzzi, D., Riedner, B., Tononi, G.

Proceedings of the National Academy of Sciences of the United States of America, 105(41):15641-15642 , October 2008 (article)

Abstract
The brain is never inactive. Neurons fire at leisurely rates most of the time, even in sleep (1), although occasionally they fire more intensely, for example, when presented with certain stimuli. Coordinated changes in the activity and excitability of many neurons underlie spontaneous fluctuations in the electroencephalogram (EEG), first observed almost a century ago. These fluctuations can be very slow (infraslow oscillations, <0.1 Hz; slow oscillations, <1 Hz; and slow waves or delta waves, 1–4 Hz), intermediate (theta, 4–8 Hz; alpha, 8–12 Hz; and beta, 13–20 Hz), and fast (gamma, >30 Hz). Moreover, slower fluctuations appear to group and modulate faster ones (1, 2). The BOLD signal underlying functional magnetic resonance imaging (fMRI) also exhibits spontaneous fluctuations at the timescale of tens of seconds (infraslow, <0.1 Hz), which occurs at all times, during task-performance as well as during quiet wakefulness, rapid eye movement (REM) sleep, and non-REM sleep (NREM). Although the precise mechanism underlying the BOLD signal is still being investigated (3–5), it is becoming clear that spontaneous BOLD fluctuations are not just noise, but are tied to fluctuations in neural activity. In this issue of PNAS, He et al. (6) have been able to directly investigate the relationship between BOLD fluctuations and fluctuations in the brain's electrical activity in human subjects. He et al. (6) took advantage of the seminal observation by Biswal et al. (7) that spontaneous BOLD fluctuations in regions belonging to the same functional system are strongly correlated. As expected, He et al. saw that fMRI BOLD fluctuations were strongly correlated among regions within the sensorimotor system, but much less between sensorimotor regions and control regions (nonsensorimotor). The twist was that they did the fMRI recordings in subjects who had been implanted with intracranial electrocorticographic (ECoG) electrodes to record regional EEG signals (to localize epileptic foci). In a separate session, He et al. examined correlations in EEG signals between different regions. They found that, just like the BOLD fluctuations, infraslow and slow fluctuations in the EEG signal from sensorimotor-sensorimotor pairs of electrodes were positively correlated, whereas signals from sensorimotor-control pairs were not. Moreover, the correlation persisted across arousal states: in waking, NREM, and REM sleep. Finally, using several statistical approaches, they found a remarkable correspondence between regional correlations in the infraslow BOLD signal and regional correlations in the infraslow-slow EEG signal (<0.5 Hz or 1–4 Hz). Notably, another report has just appeared showing that mirror sites of auditory cortex across the two hemispheres, which show correlated BOLD activity, also show correlated infraslow EEG fluctuations recorded with ECoG electrodes (8). In this case, the correlated fluctuations reflected infraslow changes in EEG power in the gamma range [however, no significant correlations were found for slow ECoG frequencies (1–4 Hz)].

Web DOI [BibTex]

Web DOI [BibTex]


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Mixture Models for Protein Structure Ensembles

Hirsch, M., Habeck, M.

Bioinformatics, 24(19):2184-2192, October 2008 (article)

Web DOI [BibTex]

Web DOI [BibTex]


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Structure of the human voltage-dependent anion channel

Bayrhuber, M., Meins, T., Habeck, M., Becker, S., Giller, K., Villinger, S., Vonrhein, C., Griesinger, C., Zweckstetter, M., Zeth, K.

Proceedings of the National Academy of Sciences of the United States of America, 105(40):15370-15375, October 2008 (article)

Abstract
The voltage-dependent anion channel (VDAC), also known as mitochondrial porin, is the most abundant protein in the mitochondrial outer membrane (MOM). VDAC is the channel known to guide the metabolic flux across the MOM and plays a key role in mitochondrially induced apoptosis. Here, we present the 3D structure of human VDAC1, which was solved conjointly by NMR spectroscopy and x-ray crystallography. Human VDAC1 (hVDAC1) adopts a &amp;#946;-barrel architecture composed of 19 &amp;#946;-strands with an &amp;#945;-helix located horizontally midway within the pore. Bioinformatic analysis indicates that this channel architecture is common to all VDAC proteins and is adopted by the general import pore TOM40 of mammals, which is also located in the MOM.

Web DOI [BibTex]

Web DOI [BibTex]


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MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration

Hofmann, M., Steinke, F., Scheel, V., Charpiat, G., Farquhar, J., Aschoff, P., Brady, M., Schölkopf, B., Pichler, B.

Journal of Nuclear Medicine, 49(11):1875-1883, October 2008 (article)

Abstract
For quantitative PET information, correction of tissue photon attenuation is mandatory. Generally in conventional PET, the attenuation map is obtained from a transmission scan, which uses a rotating radionuclide source, or from the CT scan in a combined PET/CT scanner. In the case of PET/MRI scanners currently under development, insufficient space for the rotating source exists; the attenuation map can be calculated from the MR image instead. This task is challenging because MR intensities correlate with proton densities and tissue-relaxation properties, rather than with attenuation-related mass density. METHODS: We used a combination of local pattern recognition and atlas registration, which captures global variation of anatomy, to predict pseudo-CT images from a given MR image. These pseudo-CT images were then used for attenuation correction, as the process would be performed in a PET/CT scanner. RESULTS: For human brain scans, we show on a database of 17 MR/CT image pairs that our method reliably enables e stimation of a pseudo-CT image from the MR image alone. On additional datasets of MRI/PET/CT triplets of human brain scans, we compare MRI-based attenuation correction with CT-based correction. Our approach enables PET quantification with a mean error of 3.2% for predefined regions of interest, which we found to be clinically not significant. However, our method is not specific to brain imaging, and we show promising initial results on 1 whole-body animal dataset. CONCLUSION: This method allows reliable MRI-based attenuation correction for human brain scans. Further work is necessary to validate the method for whole-body imaging.

Web DOI [BibTex]

Web DOI [BibTex]


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Support Vector Machines and Kernels for Computational Biology

Ben-Hur, A., Ong, C., Sonnenburg, S., Schölkopf, B., Rätsch, G.

PLoS Computational Biology, 4(10: e1000173):1-10, October 2008 (article)

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Approximations for Binary Gaussian Process Classification

Nickisch, H., Rasmussen, C.

Journal of Machine Learning Research, 9, pages: 2035-2078, October 2008 (article)

Abstract
We provide a comprehensive overview of many recent algorithms for approximate inference in Gaussian process models for probabilistic binary classification. The relationships between several approaches are elucidated theoretically, and the properties of the different algorithms are corroborated by experimental results. We examine both 1) the quality of the predictive distributions and 2) the suitability of the different marginal likelihood approximations for model selection (selecting hyperparameters) and compare to a gold standard based on MCMC. Interestingly, some methods produce good predictive distributions although their marginal likelihood approximations are poor. Strong conclusions are drawn about the methods: The Expectation Propagation algorithm is almost always the method of choice unless the computational budget is very tight. We also extend existing methods in various ways, and provide unifying code implementing all approaches.

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PDF PDF [BibTex]


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Accurate NMR Structures Through Minimization of an Extended Hybrid Energy

Nilges, M., Bernard, A., Bardiaux, B., Malliavin, T., Habeck, M., Rieping, W.

Structure, 16(9):1305-1312, September 2008 (article)

Abstract
The use of generous distance bounds has been the hallmark of NMR structure determination. However, bounds necessitate the estimation of data quality before the calculation, reduce the information content, introduce human bias, and allow for major errors in the structures. Here, we propose a new rapid structure calculation scheme based on Bayesian analysis. The minimization of an extended energy function, including a new type of distance restraint and a term depending on the data quality, results in an estimation of the data quality in addition to coordinates. This allows for the determination of the optimal weight on the experimental information. The resulting structures are of better quality and closer to the X–ray crystal structure of the same molecule. With the new calculation approach, the analysis of discrepancies from the target distances becomes meaningful. The strategy may be useful in other applications—for example, in homology modeling.

PDF DOI [BibTex]

PDF DOI [BibTex]


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Similarity, Kernels, and the Triangle Inequality

Jäkel, F., Schölkopf, B., Wichmann, F.

Journal of Mathematical Psychology, 52(5):297-303, September 2008 (article)

Abstract
Similarity is used as an explanatory construct throughout psychology and multidimensional scaling (MDS) is the most popular way to assess similarity. In MDS, similarity is intimately connected to the idea of a geometric representation of stimuli in a perceptual space. Whilst connecting similarity and closeness of stimuli in a geometric representation may be intuitively plausible, Tversky and Gati [Tversky, A., Gati, I. (1982). Similarity, separability, and the triangle inequality. Psychological Review, 89(2), 123–154] have reported data which are inconsistent with the usual geometric representations that are based on segmental additivity. We show that similarity measures based on Shepard’s universal law of generalization [Shepard, R. N. (1987). Toward a universal law of generalization for psychologica science. Science, 237(4820), 1317–1323] lead to an inner product representation in a reproducing kernel Hilbert space. In such a space stimuli are represented by their similarity to all other stimuli. This representation, based on Shepard’s law, has a natural metric that does not have additive segments whilst still retaining the intuitive notion of connecting similarity and distance between stimuli. Furthermore, this representation has the psychologically appealing property that the distance between stimuli is bounded.

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PDF Web DOI [BibTex]