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48 results (View BibTeX file of all listed publications)

2018

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Poster Abstract: Toward Fast Closed-loop Control over Multi-hop Low-power Wireless Networks

Mager, F., Baumann, D., Trimpe, S., Zimmerling, M.

Proceedings of the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 158-159, Porto, Portugal, April 2018 (poster)

ics

DOI Project Page [BibTex]

2018

ics Mager, F., Baumann, D., Trimpe, S., Zimmerling, M. Poster Abstract: Toward Fast Closed-loop Control over Multi-hop Low-power Wireless Networks Proceedings of the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 158-159, Porto, Portugal, April 2018 (poster)

DOI Project Page [BibTex]

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Representation of sensory uncertainty in macaque visual cortex

Goris, R., Henaff, O., Meding, K.

Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)

ei

[BibTex]

ei Goris, R., Henaff, O., Meding, K. Representation of sensory uncertainty in macaque visual cortex Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)

[BibTex]

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Generalized phase locking analysis of electrophysiology data

Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N. K., Besserve, M.

7th AREADNE Conference on Research in Encoding and Decoding of Neural Ensembles, 2018 (poster)

ei

link (url) Project Page [BibTex]

ei Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N. K., Besserve, M. Generalized phase locking analysis of electrophysiology data 7th AREADNE Conference on Research in Encoding and Decoding of Neural Ensembles, 2018 (poster)

link (url) Project Page [BibTex]

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Photorealistic Video Super Resolution

Pérez-Pellitero, E., Sajjadi, M. S. M., Hirsch, M., Schölkopf, B.

Workshop and Challenge on Perceptual Image Restoration and Manipulation (PIRM) at the 15th European Conference on Computer Vision (ECCV), 2018 (poster)

ei

[BibTex]

ei Pérez-Pellitero, E., Sajjadi, M. S. M., Hirsch, M., Schölkopf, B. Photorealistic Video Super Resolution Workshop and Challenge on Perceptual Image Restoration and Manipulation (PIRM) at the 15th European Conference on Computer Vision (ECCV), 2018 (poster)

[BibTex]

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Retinal image quality of the human eye across the visual field

Meding, K., Hirsch, M., Wichmann, F. A.

14th Biannual Conference of the German Society for Cognitive Science (KOGWIS 2018), 2018 (poster)

ei

[BibTex]

ei Meding, K., Hirsch, M., Wichmann, F. A. Retinal image quality of the human eye across the visual field 14th Biannual Conference of the German Society for Cognitive Science (KOGWIS 2018), 2018 (poster)

[BibTex]

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Nanorobots propel through the eye

Zhiguang Wu, J. T. H. J. Q. W. M. S. F. Z. Z. W. M. D. S. S. T. Q. P. F.

Max Planck Society, 2018 (mpi_year_book)

Abstract
Scientists at the Max Planck Institute for Intelligent Systems in Stuttgart developed specially coated nanometer-sized robots that could be moved actively through dense tissue like the vitreous of the eye. So far, the transport of such nano-vehicles has only been demonstrated in model systems or biological fluids, but not in real tissue. Our work constitutes one step further towards nanorobots becoming minimally-invasive tools for precisely delivering medicine to where it is needed.

pf

link (url) [BibTex]

2010

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Similarities in resting state and feature-driven activity: Non-parametric evaluation of human fMRI

Shelton, J., Blaschko, M., Gretton, A., Müller, J., Fischer, E., Bartels, A.

NIPS Workshop on Learning and Planning from Batch Time Series Data, December 2010 (poster)

ei

PDF Web [BibTex]

2010

ei Shelton, J., Blaschko, M., Gretton, A., Müller, J., Fischer, E., Bartels, A. Similarities in resting state and feature-driven activity: Non-parametric evaluation of human fMRI NIPS Workshop on Learning and Planning from Batch Time Series Data, December 2010 (poster)

PDF Web [BibTex]

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Augmentation of fMRI Data Analysis using Resting State Activity and Semi-supervised Canonical Correlation Analysis

Shelton, JA., Blaschko, MB., Bartels, A.

NIPS Women in Machine Learning Workshop (WiML), December 2010 (poster)

Abstract
Resting state activity is brain activation that arises in the absence of any task, and is usually measured in awake subjects during prolonged fMRI scanning sessions where the only instruction given is to close the eyes and do nothing. It has been recognized in recent years that resting state activity is implicated in a wide variety of brain function. While certain networks of brain areas have different levels of activation at rest and during a task, there is nevertheless significant similarity between activations in the two cases. This suggests that recordings of resting state activity can be used as a source of unlabeled data to augment kernel canonical correlation analysis (KCCA) in a semisupervised setting. We evaluate this setting empirically yielding three main results: (i) KCCA tends to be improved by the use of Laplacian regularization even when no additional unlabeled data are available, (ii) resting state data seem to have a similar marginal distribution to that recorded during the execution of a visual processing task implying largely similar types of activation, and (iii) this source of information can be broadly exploited to improve the robustness of empirical inference in fMRI studies, an inherently data poor domain.

ei

PDF Web [BibTex]

ei Shelton, JA., Blaschko, MB., Bartels, A. Augmentation of fMRI Data Analysis using Resting State Activity and Semi-supervised Canonical Correlation Analysis NIPS Women in Machine Learning Workshop (WiML), December 2010 (poster)

PDF Web [BibTex]

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High frequency phase-spike synchronization of extracellular signals modulates causal interactions in monkey primary visual cortex

Besserve, M., Murayama, Y., Schölkopf, B., Logothetis, N., Panzeri, S.

40(616.2), 40th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2010 (poster)

Abstract
Functional correlates of Rhythms in the gamma band (30-100Hz) are observed in the mammalian brain with a large variety of functional correlates. Nevertheless, their functional role is still debated. One way to disentangle this issue is to go beyond usual correlation analysis and apply causality measures that quantify the directed interactions between the gamma rhythms and other aspects of neural activity. These measures can be further compared with other aspects of neurophysicological signals to find markers of neural interactions. In a recent study, we analyzed extracellular recordings in the primary visual cortex of 4 anesthetized macaques during the presentation of movie stimuli using a causality measure named Transfer Entropy. We found causal interactions between high frequency gamma rhythms (60-100Hz) recorded in different electrodes, involving in particular their phase, and between the gamma phase and spiking activity quantified by the instantaneous envelope of the MUA band (1-3kHz). Here, we further investigate in the same dataset the meaning of these phase-MUA and phase-phase causal interactions by studying the distribution of phases at multiple recording sites at lags around the occurrence of spiking events. First, we found a sharpening of the gamma phase distribution in one electrode when spikes are occurring in other recording site. This phenomena appeared as a form of phase-spike synchronization and was quantified by an information theoretic measure. We found this measure correlates significantly with phase-MUA causal interactions. Additionally, we quantified in a similar way the interplay between spiking and the phase difference between two recording sites (reflecting the well-know concept of phase synchronization). We found that, depending on the couple of recording site, spiking can correlate either with a phase synchronization or with a desynchronization with respect to the baseline. This effect correlates very well with the phase-phase causality measure. These results provide evidence for high frequency phase-spike synchronization to reflect communication between distant neural populations in V1. Conversely, both phase synchronization or desynchronization may favor neural communication between recording sites. This new result, which contrasts with current hypothesis on the role of phase synchronization, could be interpreted as the presence of inhibitory interactions that are suppressed by desynchronization. Finally, our findings give new insights into the role of gamma rhythms in regulating local computation in the visual cortex.

ei

Web [BibTex]

ei Besserve, M., Murayama, Y., Schölkopf, B., Logothetis, N., Panzeri, S. High frequency phase-spike synchronization of extracellular signals modulates causal interactions in monkey primary visual cortex 40(616.2), 40th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2010 (poster)

Web [BibTex]

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Attenuation Correction for Whole Body PET/MR: Quantitative Evaluation and Lung Attenuation Estimation with Consistency Information

Bezrukov, I., Hofmann, M., Aschoff, P., Beyer, T., Mantlik, F., Pichler, B., Schölkopf, B.

2010(M13-122), 2010 Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), November 2010 (poster)

ei

[BibTex]

ei Bezrukov, I., Hofmann, M., Aschoff, P., Beyer, T., Mantlik, F., Pichler, B., Schölkopf, B. Attenuation Correction for Whole Body PET/MR: Quantitative Evaluation and Lung Attenuation Estimation with Consistency Information 2010(M13-122), 2010 Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), November 2010 (poster)

[BibTex]

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PET/MRI: Observation of Non-Isotropic Positron Distribution in High Magnetic Fields and Its Diagnostic Impact

Kolb, A., Hofmann, M., Sauter, A., Liu, C., Schölkopf, B., Pichler, B.

2010 Nuclear Science Symposium and Medical Imaging Conference, 2010(M18-119):1, November 2010 (poster)

ei

Web [BibTex]

ei Kolb, A., Hofmann, M., Sauter, A., Liu, C., Schölkopf, B., Pichler, B. PET/MRI: Observation of Non-Isotropic Positron Distribution in High Magnetic Fields and Its Diagnostic Impact 2010 Nuclear Science Symposium and Medical Imaging Conference, 2010(M18-119):1, November 2010 (poster)

Web [BibTex]

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Probabilistic Assignment of Chemical Shift Data for Semi-Automatic Amino Acid Recognition

Hooge, J.

11(10):30, 11th Conference of Junior Neuroscientists of T{\"u}bingen (NeNa), October 2010 (poster)

Abstract
manner. First the backbone resonances are assigned. This is usually achieved from sequential information provided by three chemical shifts: CA, CB and C’. Once the sequence is solved, the second assignment step takes place. For this purpose, the CA-CB and HA chemical shifts are used as a start point for assignment of the side chain resonances, thus connecting the backbone resonances to their respective side chains. This strategy is unfortunately limited by the size of the protein due to increasing signal overlap and missing signals. Therefore, amino acid recognition is in many cases not possible as the CA-CB chemical shift pattern is not sufficient to discriminate between the 20 amino acids. As a result, the first step of the strategy described above remains tedious and time consuming. The combination of modern NMR techniques with new spectrometers now provide information that was not always accessible in the past, due to sensitivity problems. These experiments can be applied efficiently to measure a protein size up to 45 kDa and furthermore provide a unique combination of sequential carbon spin system information. The assignment process can thus benefit from a maximum knowledge input, containing âallâ backbone and side chain chemical shifts as well as an immediate amino acid recognition from the side chain spin system. We propose to extend the software PASTA (Protein ASsignment by Threshold Accepting) to achieve a general sequential assignment of backbone and side-chain resonances in a semi- to fullautomatic per-residue approach. PASTA will offer the possibility to achieve the sequential assignment using any kind of chemical shifts (carbons and/or protons) that can provide sequential information combined with an amino acid recognition feature based on carbon spin system analysis.

ei

PDF [BibTex]

ei Hooge, J. Probabilistic Assignment of Chemical Shift Data for Semi-Automatic Amino Acid Recognition 11(10):30, 11th Conference of Junior Neuroscientists of T{\"u}bingen (NeNa), October 2010 (poster)

PDF [BibTex]

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Generalizing Demonstrated Actions in Manipulation Tasks

Kroemer, O., Detry, R., Piater, J., Peters, J.

IROS 2010 Workshop on Grasp Planning and Task Learning by Imitation, 2010, pages: 1, October 2010 (poster)

Abstract
Programming-by-demonstration promises to significantly reduce the burden of coding robots to perform new tasks. However, service robots will be presented with a variety of different situations that were not specifically demonstrated to it. In such cases, the robot must autonomously generalize its learned motions to these new situations. We propose a system that can generalize movements to new target locations and even new objects. The former is achieved by using a task-specific coordinate system together with dynamical systems motor primitives. Generalizing actions to new objects is a more complex problem, which we solve by treating it as a continuum-armed bandits problem. Using the bandits framework, we can efficiently optimize the learned action for a specific object. The proposed method was implemented on a real robot and succesfully adapted the grasping action to three different objects. Although we focus on grasping as an example of a task, the proposed methods are much more widely applicable to robot manipulation tasks.

ei

PDF Web [BibTex]

ei Kroemer, O., Detry, R., Piater, J., Peters, J. Generalizing Demonstrated Actions in Manipulation Tasks IROS 2010 Workshop on Grasp Planning and Task Learning by Imitation, 2010, pages: 1, October 2010 (poster)

PDF Web [BibTex]

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Inhomogeneous Positron Range Effects in High Magnetic Fields might Cause Severe Artefacts in PET/MRI

Kolb, A., Hofmann, M., Sauter, A., Liu, C., Eriksson, L., Pichler, B.

(0305B), 2010 World Molecular Imaging Congress (WMIC), September 2010 (poster)

Abstract
The combination of PET and MRI is an emerging field of current research. It is known that the positron range is shortened in high magnetic fields (MF), leading to an improved resolution in PET images. Interestingly, only the fraction of positron range (PR) orthogonal to the MF is reduced and the fraction along the MF is not affected and yields to a non-isotropic count distribution. We measured the PR effect with PET isotopes like F-18, Cu-64, C-11, N-13 and Ga-68. A piece of paper (1 cm2) was soaked with each isotope and placed in the cFOV of a clinical 3T BrainPET/MR scanner. A polyethylene board (PE) was placed as a positron (β+) stopper with an axial distance of 3 cm from the soaked paper. The area under the peaks of one pixel wide profiles along the z-axis in coronal images was compared. Based on these measurements we confirmed our data in organic tissue. A larynx/trachea and lung of a butchered swine were injected with a mixture of NiSO4 for T1 MRI signals and Ga-68, simulating tumor lesions in the respiratory tract. The trachea/larynx were aligned in 35° to the MF lines and a small mass lesion was inserted to imitate a primary tracheal tumor whereas the larynx was injected submucosally in the lower medial part of the epiglottis. Reconstructed PET data show that the annihilated ratio of β+ at the origin position and in the PE depends on the isotope energy and the direction of the MF. The annihilation ratios of the source and PE are 52.4/47.6 (F-18), 57.5/42.5 (Cu-64), 43.7/56.7 (C-11), 31.1/68.9 (N-13) and 14.9/85.1 (Ga-68). In the swine larynx measurement, an artefact with approximately 39% of the lesion activity formed along MF lines 3cm away from the original injected position (fig.1). The data of the trachea showed two shine artefacts with a symmetric alignment along the MF lines. About 58% of the positrons annihilated at the lesion and 21% formed each artefact. The PR effects areminor in tissue of higher or equal density to water (0.096 cm-1). However, the effect is severe in low density tissue or air and might lead to misinterpretation of clinical data.

ei

Web [BibTex]

ei Kolb, A., Hofmann, M., Sauter, A., Liu, C., Eriksson, L., Pichler, B. Inhomogeneous Positron Range Effects in High Magnetic Fields might Cause Severe Artefacts in PET/MRI (0305B), 2010 World Molecular Imaging Congress (WMIC), September 2010 (poster)

Web [BibTex]

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Reinforcement Learning by Relative Entropy Policy Search

Peters, J., Mülling, K., Altun, Y.

30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 69, July 2010 (poster)

Abstract
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature convergence and implausible solutions. As first suggested in the context of covariant policy gradients, many of these problems may be addressed by constraining the information loss. In this book chapter, we continue this path of reasoning and suggest the Relative Entropy Policy Search (REPS) method. The resulting method differs significantly from previous policy gradient approaches and yields an exact update step. It works well on typical reinforcement learning benchmark problems. We will also present a real-world applications where a robot employs REPS to learn how to return balls in a game of table tennis.

ei

PDF [BibTex]

ei Peters, J., Mülling, K., Altun, Y. Reinforcement Learning by Relative Entropy Policy Search 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 69, July 2010 (poster)

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A Maximum Entropy Approach to Semi-supervised Learning

Erkan, A., Altun, Y.

30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 80, July 2010 (poster)

Abstract
Maximum entropy (MaxEnt) framework has been studied extensively in supervised learning. Here, the goal is to find a distribution p that maximizes an entropy function while enforcing data constraints so that the expected values of some (pre-defined) features with respect to p match their empirical counterparts approximately. Using different entropy measures, different model spaces for p and different approximation criteria for the data constraints yields a family of discriminative supervised learning methods (e.g., logistic regression, conditional random fields, least squares and boosting). This framework is known as the generalized maximum entropy framework. Semi-supervised learning (SSL) has emerged in the last decade as a promising field that combines unlabeled data along with labeled data so as to increase the accuracy and robustness of inference algorithms. However, most SSL algorithms to date have had trade-offs, e.g., in terms of scalability or applicability to multi-categorical data. We extend the generalized MaxEnt framework to develop a family of novel SSL algorithms. Extensive empirical evaluation on benchmark data sets that are widely used in the literature demonstrates the validity and competitiveness of the proposed algorithms.

ei

PDF PDF [BibTex]

ei Erkan, A., Altun, Y. A Maximum Entropy Approach to Semi-supervised Learning 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 80, July 2010 (poster)

PDF PDF [BibTex]

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The effect of positioning aids on PET quantification following MR-based attenuation correction (AC) in PET/MR imaging

Mantlik, F., Hofmann, M., Kupferschläger, J., Werner, M., Pichler, B., Beyer, T.

Journal of Nuclear Medicine, 51(Supplement 2):1418 , June 2010 (poster)

Abstract
Objectives: We study the quantitative effect of not accounting for the attenuation of patient positioning aids in combined PET/MR imaging. Methods: Positioning aids cannot be detected with conventional MR sequences. We mimic this effect using PET/CT data (Biograph HiRez16) with the foams removed from CT images prior to using them for CT-AC. PET/CT data were acquired using standard parameters (phantoms/patients): 120/140 kVp, 30/250 mAs, 5 mm slices, OSEM (4i, 8s, 5 mm filter) following CT-AC. First, a uniform 68Ge-cylinder was positioned centrally in the PET/CT and fixed with a vacuum mattress (10 cm thick). Second, the same cylinder was placed in 3 positioning aids from the PET/MR (BrainPET-3T). Third, 5 head/neck patients who were fixed in a vacuum mattress were selected. In all 3 studies PET recon post CT-AC based on measured CT images was used as the reference (mCT-AC). The PET/MR set-up was mimicked by segmenting the foam inserts from the measured CT images and setting their voxel values to -1000 HU (air). PET images were reconstructed using CT-AC with the segmented CT images (sCT-AC). PET images with mCT- and sCT-AC were compared. Results: sCT-AC underestimated PET voxel values in the phantom by 6.7% on average compared to mCT-AC with the vacuum mattress in place. 5% of the PET voxels were underestimated by >=10%. Not accounting for MR positioning aids during AC led to an underestimation of 2.8% following sCT-AC, with 5% of the PET voxels being underestimated by >=7% wrt mCT-AC. Preliminary evaluation of the patient data indicates a slightly higher bias from not accounting for patient positioning aids (mean: -9.1%, 5% percentile: -11.2%). Conclusions: A considerable and regionally variable underestimation of the PET activity following AC is observed when positioning aids are not accounted for. This bias may become relevant in neurological activation or dementia studies with PET/MR

ei

Web [BibTex]

ei Mantlik, F., Hofmann, M., Kupferschläger, J., Werner, M., Pichler, B., Beyer, T. The effect of positioning aids on PET quantification following MR-based attenuation correction (AC) in PET/MR imaging Journal of Nuclear Medicine, 51(Supplement 2):1418 , June 2010 (poster)

Web [BibTex]

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Multi-task Learning for Zero Training Brain-Computer Interfaces

Alamgir, M., Grosse-Wentrup, M., Altun, Y.

4th International BCI Meeting, June 2010 (poster)

Abstract
Brain-computer interfaces (BCIs) are limited in their applicability in everyday settings by the current necessity to record subject-specific calibration data prior to actual use of the BCI for communication. In this work, we utilize the framework of multitask learning to construct a BCI that can be used without any subject-specific calibration process, i.e., with zero training data. In BCIs based on EEG or MEG, the predictive function of a subject's intention is commonly modeled as a linear combination of some features derived from spatial and spectral recordings. The coefficients of this combination correspond to the importance of the features for predicting the intention of the subject. These coefficients are usually learned separately for each subject due to inter-subject variability. Principle feature characteristics, however, are known to remain invariant across subject. For example, it is well known that in motor imagery paradigms spectral power in the mu- and beta frequency ranges (roughly 8-14 Hz and 20-30 Hz, respectively) over sensorimotor areas provides most information on a subject's intention. Based on this assumption, we define the intention prediction function as a combination of subject-invariant and subject-specific models, and propose a machine learning method that infers these models jointly using data from multiple subjects. This framework leads to an out-of-the-box intention predictor, where the subject-invariant model can be employed immediately for a subject with no prior data. We present a computationally efficient method to further improve this BCI to incorporate subject-specific variations as such data becomes available. To overcome the problem of high dimensional feature spaces in this context, we further present a new method for finding the relevance of different recording channels according to actions performed by subjects. Usually, the BCI feature representation is a concatenation of spectral features extracted from different channels. This representation, however, is redundant, as recording channels at different spatial locations typically measure overlapping sources within the brain due to volume conduction. We address this problem by assuming that the relevance of different spectral bands is invariant across channels, while learning different weights for each recording electrode. This framework allows us to significantly reduce the feature space dimensionality without discarding potentially useful information. Furthermore, the resulting out-of-the-box BCI can be adapted to different experimental setups, for example EEG caps with different numbers of channels, as long as there exists a mapping across channels in different setups. We demonstrate the feasibility of our approach on a set of experimental EEG data recorded during a standard two-class motor imagery paradigm from a total of ten healthy subjects. Specifically, we show that satisfactory classification results can be achieved with zero training data, and that combining prior recordings with subject-specific calibration data substantially outperforms using subject-specific data only.

ei

Web [BibTex]

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Causal Influence of Gamma Oscillations on Performance in Brain-Computer Interfaces

Grosse-Wentrup, M., Hill, J., Schölkopf, B.

4th International BCI Meeting0, June 2010 (poster)

Abstract
Background and Objective: While machine learning approaches have led to tremendous advances in brain-computer interfaces (BCIs) in recent years (cf. [1]), there still exists a large variation in performance across subjects. Furthermore, a significant proportion of subjects appears incapable of achieving above chance-level classification accuracy [2], which to date includes all subjects in a completely locked-in state that have been trained in BCI control. Understanding the reasons for this variation in performance arguably constitutes one of the most fundamental open questions in research on BCIs. Methods & Results Using a machine learning approach, we derive a trial-wise measure of how well EEG recordings can be classified as either left- or right-hand motor imagery. Specifically, we train a support vector machine (SVM) on log-bandpower features (7-40 Hz) derived from EEG channels after spatial filtering with a surface Laplacian, and then compute the trial-wise distance of the output of the SVM from the separating hyperplane using a cross-validation procedure. We then correlate this trial-wise performance measure, computed on EEG recordings of ten healthy subjects, with log-bandpower in the gamma frequency range (55-85 Hz), and demonstrate that it is positively correlated with frontal- and occipital gamma-power and negatively correlated with centro-parietal gamma-power. This correlation is shown to be highly significant on the group level as well as in six out of ten subjects on the single-subject level. We then utilize the framework for causal inference developed by Pearl, Spirtes and others [3,4] to present evidence that gamma-power is not only correlated with BCI performance but does indeed exert a causal influence on it. Discussion and Conclusions Our results indicate that successful execution of motor imagery, and hence reliable communication by means of a BCI based on motor imagery, requires a volitional shift of gamma-power from centro-parietal to frontal and occipital regions. As such, our results provide the first non-trivial explanation for the variation in BCI performance across and within subjects. As this topographical alteration in gamma-power is likely to correspond to a specific attentional shift, we propose to provide subjects with feedback on their topographical distribution of gamma-power in order to establish the attentional state required for successful execution of motor imagery.

ei

Web [BibTex]

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Solving large-scale nonnegative least-squares

Sra, S.

16th Conference of the International Linear Algebra Society (ILAS 2010), 16, pages: 19, June 2010, based on Joint work with Dongmin Kim and Inderjit Dhillon (poster)

Abstract
We study the fundamental problem of nonnegative least squares. This problem was apparently introduced by Lawson and Hanson [1] under the name NNLS. As is evident from its name, NNLS seeks least-squares solutions that are also nonnegative. Owing to its wide-applicability numerous algorithms have been derived for NNLS, beginning from the active-set approach of Lawson and Hanson [1] leading up to the sophisticated interior-point method of Bellavia et al. [2]. We present a new algorithm for NNLS that combines projected subgradients with the non-monotonic gradient descent idea of Barzilai and Borwein [3]. Our resulting algorithm is called BBSG, and we guarantee its convergence by exploiting properties of NNLS in conjunction with projected subgradients. BBSG is surprisingly simple and scales well to large problems. We substantiate our claims by empirically evaluating BBSG and comparing it with established convex solvers and specialized NNLS algorithms. The numerical results suggest that BBSG is a practical method for solving large-scale NNLS problems.

ei

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ei Sra, S. Solving large-scale nonnegative least-squares 16th Conference of the International Linear Algebra Society (ILAS 2010), 16, pages: 19, June 2010, based on Joint work with Dongmin Kim and Inderjit Dhillon (poster)

PDF Web [BibTex]

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Simultaneous PET/MRI for the evaluation of hemato-oncological diseases with lower extremity manifestations

Sauter, A., Horger, M., Boss, A., Kolb, A., Mantlik, F., Kanz, L., Pfannenberg, C., Stegger, L., Claussen, C., Pichler, B.

Journal of Nuclear Medicine, 51(Supplement 2):1001 , June 2010 (poster)

Abstract
Objectives: The study purpose is the evaluation of patients, suffering from hemato-oncological disease with complications at the lower extremities, using simultaneous PET/MRI. Methods: Until now two patients (chronic active graft-versus-host-disease [GvHD], B-non Hodgkin lymphoma [B-NHL]) before and after therapy were examined in a 3-Tesla-BrainPET/MRI hybrid system following F-18-FDG-PET/CT. Simultaneous static PET (1200 sec.) and MRI scans (T1WI, T2WI, post-CA) were acquired. Results: Initial results show the feasibility of using hybrid PET/MRI-technology for musculoskeletal imaging of the lower extremities. Simultaneous PET and MRI could be acquired in diagnostic quality. Before treatment our patient with GvHD had a high fascia and muscle FDG uptake, possibly due to muscle encasement. T2WI and post gadolinium T1WI revealed a fascial thickening and signs of inflammation. After therapy with steroids followed by imatinib the patient’s symptoms improved while, the muscular FDG uptake droped whereas the MRI signal remained unchanged. We assume that fascial elasticity improved during therapy despite persistance of fascial thickening. The examination of the second patient with B-NHL manifestation in the tibia showed a significant signal and uptake decrease in the bone marrow and surrounding lesions in both, MRI and PET after therapy with rituximab. The lack of residual FDG-uptake proved superior to MRI information alone helping for exclusion of vital tumor. Conclusions: Combined PET/MRI is a powerful tool to monitor diseases requiring high soft tissue contrast along with molecular information from the FDG uptake.

ei

Web [BibTex]

ei Sauter, A., Horger, M., Boss, A., Kolb, A., Mantlik, F., Kanz, L., Pfannenberg, C., Stegger, L., Claussen, C., Pichler, B. Simultaneous PET/MRI for the evaluation of hemato-oncological diseases with lower extremity manifestations Journal of Nuclear Medicine, 51(Supplement 2):1001 , June 2010 (poster)

Web [BibTex]

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Solving large-scale nonnegative least squares using an adaptive non-monotonic method

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

24th European Conference on Operational Research (EURO 2010), 24, pages: 223, April 2010 (poster)

Abstract
We present an efficient algorithm for large-scale non-negative least-squares (NNLS). We solve NNLS by extending the unconstrained quadratic optimization method of Barzilai and Borwein (BB) to handle nonnegativity constraints. Our approach is simple yet efficient. It differs from other constrained BB variants as: (i) it uses a specific subset of variables for computing BB steps; and (ii) it scales these steps adaptively to ensure convergence. We compare our method with both established convex solvers and specialized NNLS methods, and observe highly competitive empirical performance.

ei

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ei Sra, S., Kim, D., Dhillon, I. Solving large-scale nonnegative least squares using an adaptive non-monotonic method 24th European Conference on Operational Research (EURO 2010), 24, pages: 223, April 2010 (poster)

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Sparse regression via a trust-region proximal method

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

24th European Conference on Operational Research (EURO 2010), 24, pages: 278, April 2010 (poster)

Abstract
We present a method for sparse regression problems. Our method is based on the nonsmooth trust-region framework that minimizes a sum of smooth convex functions and a nonsmooth convex regularizer. By employing a separable quadratic approximation to the smooth part, the method enables the use of proximity operators, which in turn allow tackling the nonsmooth part efficiently. We illustrate our method by implementing it for three important sparse regression problems. In experiments with synthetic and real-world large-scale data, our method is seen to be competitive, robust, and scalable.

ei

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ei Kim, D., Sra, S., Dhillon, I. Sparse regression via a trust-region proximal method 24th European Conference on Operational Research (EURO 2010), 24, pages: 278, April 2010 (poster)

PDF [BibTex]

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PAC-Bayesian Bounds for Discrete Density Estimation and Co-clustering Analysis

Seldin, Y., Tishby, N.

Workshop "Foundations and New Trends of PAC Bayesian Learning", 2010, March 2010 (poster)

Abstract
We applied PAC-Bayesian framework to derive gen- eralization bounds for co-clustering1. The analysis yielded regularization terms that were absent in the preceding formulations of this task. The bounds sug- gested that co-clustering should optimize a trade-off between its empirical performance and the mutual in- formation that the cluster variables preserve on row and column indices. Proper regularization enabled us to achieve state-of-the-art results in prediction of the missing ratings in the MovieLens collaborative filtering dataset. In addition a PAC-Bayesian bound for discrete den- sity estimation was derived. We have shown that the PAC-Bayesian bound for classification is a spe- cial case of the PAC-Bayesian bound for discrete den- sity estimation. We further introduced combinatorial priors to PAC-Bayesian analysis. The combinatorial priors are more appropriate for discrete domains, as opposed to Gaussian priors, the latter of which are suitable for continuous domains. It was shown that combinatorial priors lead to regularization terms in the form of mutual information.

ei

PDF Web [BibTex]

ei Seldin, Y., Tishby, N. PAC-Bayesian Bounds for Discrete Density Estimation and Co-clustering Analysis Workshop "Foundations and New Trends of PAC Bayesian Learning", 2010, March 2010 (poster)

PDF Web [BibTex]

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Learning the Reward Model of Dialogue POMDPs

Boularias, A., Chinaei, H., Chaib-Draa, B.

NIPS Workshop on Machine Learning for Assistive Technology (MLAT-2010), 2010 (poster)

ei

[BibTex]

ei Boularias, A., Chinaei, H., Chaib-Draa, B. Learning the Reward Model of Dialogue POMDPs NIPS Workshop on Machine Learning for Assistive Technology (MLAT-2010), 2010 (poster)

[BibTex]

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Erste Erfahrungen bei der Beurteilung hämato-onkologischer Krankheitsmanifestationen an den Extremitäten mit einem PET/MRT-Hybridsystem.

Sauter, A., Boss, A., Kolb, A., Mantlik, F., Bethge, W., Kanz, L., Pfannenberg, C., Stegger, L., Pichler, B., Claussen, C., Horger, M.

Thieme Verlag, Stuttgart, Germany, 91. Deutscher R{\"o}ntgenkongress, 2010 (poster)

ei

Web DOI [BibTex]

ei Sauter, A., Boss, A., Kolb, A., Mantlik, F., Bethge, W., Kanz, L., Pfannenberg, C., Stegger, L., Pichler, B., Claussen, C., Horger, M. Erste Erfahrungen bei der Beurteilung hämato-onkologischer Krankheitsmanifestationen an den Extremitäten mit einem PET/MRT-Hybridsystem. Thieme Verlag, Stuttgart, Germany, 91. Deutscher R{\"o}ntgenkongress, 2010 (poster)

Web DOI [BibTex]

2009

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Clinical PET/MRI-System and Its Applications with MRI Based Attenuation Correction

Kolb, A., Hofmann, M., Sossi, V., Wehrl, H., Sauter, A., Schmid, A., Schlemmer, H., Claussen, C., Pichler, B.

IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2009), 2009, pages: 1, October 2009 (poster)

Abstract
Clinical PET/MRI is an emerging new hybrid imaging modality. In addition to provide an unique possibility for multifunctional imaging with temporally and spatially matched data, it also provides anatomical information that can also be used for attenuation correction with no radiation exposure to the subjects. A plus of combined compared to sequential PET and MR imaging is the reduction of total scan time. Here we present our initial experience with a hybrid brain PET/MRI system. Due to the ethical approval patient scans could only be performed after a diagnostic PET/CT. We estimate that in approximately 50% of the cases PET/MRI was of superior diagnostic value compared to PET/CT and was able to provide additional information, such as DTI, spectroscopy and Time Of Flight (TOF) angiography. Here we present 3 patient cases in oncology, a retropharyngeal carcinoma in neurooncology, a relapsing meningioma and in neurology a pharyngeal carcinoma in addition to an infraction of the right hemisphere. For quantitative PET imaging attenuation correction is obligatory. In current PET/MRI setup we used our MRI based atlas method for calculating the mu-map for attenuation correction. MR-based attenuation correction accuracy was quantitatively compared to CT-based PET attenuation correction. Extensive studies to assess potential mutual interferences between PET and MR imaging modalities as well as NEMA measurements have been performed. The first patient studies as well as the phantom tests clearly demonstrated the overall good imaging performance of this first human PET/MRI system. Ongoing work concentrates on advanced normalization and reconstruction methods incorporating count-rate based algorithms.

ei

Web [BibTex]

2009

ei Kolb, A., Hofmann, M., Sossi, V., Wehrl, H., Sauter, A., Schmid, A., Schlemmer, H., Claussen, C., Pichler, B. Clinical PET/MRI-System and Its Applications with MRI Based Attenuation Correction IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2009), 2009, pages: 1, October 2009 (poster)

Web [BibTex]

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A flowering-time gene network model for association analysis in Arabidopsis thaliana

Klotzbücher, K., Kobayashi, Y., Shervashidze, N., Borgwardt, K., Weigel, D.

2009(39):95-96, German Conference on Bioinformatics (GCB '09), September 2009 (poster)

Abstract
In our project we want to determine a set of single nucleotide polymorphisms (SNPs), which have a major effect on the flowering time of Arabidopsis thaliana. Instead of performing a genome-wide association study on all SNPs in the genome of Arabidopsis thaliana, we examine the subset of SNPs from the flowering-time gene network model. We are interested in how the results of the association study vary when using only the ascertained subset of SNPs from the flowering network model, and when additionally using the information encoded by the structure of the network model. The network model is compiled from the literature by manual analysis and contains genes which have been found to affect the flowering time of Arabidopsis thaliana [Far+08; KW07]. The genes in this model are annotated with the SNPs that are located in these genes, or in near proximity to them. In a baseline comparison between the subset of SNPs from the graph and the set of all SNPs, we omit the structural information and calculate the correlation between the individual SNPs and the flowering time phenotype by use of statistical methods. Through this we can determine the subset of SNPs with the highest correlation to the flowering time. In order to further refine this subset, we include the additional information provided by the network structure by conducting a graph-based feature pre-selection. In the further course of this project we want to validate and examine the resulting set of SNPs and their corresponding genes with experimental methods.

ei

PDF Web [BibTex]

ei Klotzbücher, K., Kobayashi, Y., Shervashidze, N., Borgwardt, K., Weigel, D. A flowering-time gene network model for association analysis in Arabidopsis thaliana 2009(39):95-96, German Conference on Bioinformatics (GCB '09), September 2009 (poster)

PDF Web [BibTex]

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Initial Data from a first PET/MRI-System and its Applications in Clinical Studies Using MRI Based Attenuation Correction

Kolb, A., Hofmann, M., Sossi, V., Wehrl, H., Sauter, A., Schmid, A., Judenhofer, M., Schlemmer, H., Claussen, C., Pichler, B.

2009 World Molecular Imaging Congress, 2009, pages: 1200, September 2009 (poster)

ei

Web [BibTex]

ei Kolb, A., Hofmann, M., Sossi, V., Wehrl, H., Sauter, A., Schmid, A., Judenhofer, M., Schlemmer, H., Claussen, C., Pichler, B. Initial Data from a first PET/MRI-System and its Applications in Clinical Studies Using MRI Based Attenuation Correction 2009 World Molecular Imaging Congress, 2009, pages: 1200, September 2009 (poster)

Web [BibTex]

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A High-Speed Object Tracker from Off-the-Shelf Components

Lampert, C., Peters, J.

First IEEE Workshop on Computer Vision for Humanoid Robots in Real Environments at ICCV 2009, 1, pages: 1, September 2009 (poster)

Abstract
We introduce RTblob, an open-source real-time vision system for 3D object detection that achieves over 200 Hz tracking speed with only off-the-shelf hardware component. It allows fast and accurate tracking of colored objects in 3D without expensive and often custom-built hardware, instead making use of the PC graphics cards for the necessary image processing operations.

ei

PDF Web [BibTex]

ei Lampert, C., Peters, J. A High-Speed Object Tracker from Off-the-Shelf Components First IEEE Workshop on Computer Vision for Humanoid Robots in Real Environments at ICCV 2009, 1, pages: 1, September 2009 (poster)

PDF Web [BibTex]

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Estimating Critical Stimulus Features from Psychophysical Data: The Decision-Image Technique Applied to Human Faces

Macke, J., Wichmann, F.

Journal of Vision, 9(8):31, 9th Annual Meeting of the Vision Sciences Society (VSS), August 2009 (poster)

Abstract
One of the main challenges in the sensory sciences is to identify the stimulus features on which the sensory systems base their computations: they are a pre-requisite for computational models of perception. We describe a technique---decision-images--- for extracting critical stimulus features based on logistic regression. Rather than embedding the stimuli in noise, as is done in classification image analysis, we want to infer the important features directly from physically heterogeneous stimuli. A Decision-image not only defines the critical region-of-interest within a stimulus but is a quantitative template which defines a direction in stimulus space. Decision-images thus enable the development of predictive models, as well as the generation of optimized stimuli for subsequent psychophysical investigations. Here we describe our method and apply it to data from a human face discrimination experiment. We show that decision-images are able to predict human responses not only in terms of overall percent correct but are able to predict, for individual observers, the probabilities with which individual faces are (mis-) classified. We then test the predictions of the models using optimized stimuli. Finally, we discuss possible generalizations of the approach and its relationships with other models.

ei

Web DOI [BibTex]

ei Macke, J., Wichmann, F. Estimating Critical Stimulus Features from Psychophysical Data: The Decision-Image Technique Applied to Human Faces Journal of Vision, 9(8):31, 9th Annual Meeting of the Vision Sciences Society (VSS), August 2009 (poster)

Web DOI [BibTex]

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Semi-supervised Analysis of Human fMRI Data

Shelton, JA., Blaschko, MB., Lampert, CH., Bartels, A.

Berlin Brain Computer Interface Workshop on Advances in Neurotechnology, 2009, pages: 1, July 2009 (poster)

Abstract
Kernel Canonical Correlation Analysis (KCCA) is a general technique for subspace learning that incorporates principal components analysis (PCA) and Fisher linear discriminant analysis (LDA) as special cases. By finding directions that maximize correlation, CCA learns representations tied more closely to underlying process generating the the data and can ignore high-variance noise directions. However, for data where acquisition in a given modality is expensive or otherwise limited, CCA may suffer from small sample effects. We propose to use semisupervised Laplacian regularization to utilize data that are present in only one modality. This approach is able to find highly correlated directions that also lie along the data manifold, resulting in a more robust estimate of correlated subspaces. Functional magnetic resonance imaging (fMRI) acquired data are naturally amenable to subspace techniques as data are well aligned. fMRI data of the human brain are a particularly interesting candidate. In this study we implemented various supervised and semi-supervised versions of CCA on human fMRI data, with regression to single and multivariate labels (corresponding to video content subjects viewed during the image acquisition). In each variate condition, the semi-supervised variants of CCA performed better than the supervised variants, including a supervised variant with Laplacian regularization. We additionally analyze the weights learned by the regression in order to infer brain regions that are important to different types of visual processing.

ei

PDF Web [BibTex]

ei Shelton, JA., Blaschko, MB., Lampert, CH., Bartels, A. Semi-supervised Analysis of Human fMRI Data Berlin Brain Computer Interface Workshop on Advances in Neurotechnology, 2009, pages: 1, July 2009 (poster)

PDF Web [BibTex]

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Optimization of k-Space Trajectories by Bayesian Experimental Design

Seeger, M., Nickisch, H., Pohmann, R., Schölkopf, B.

17(2627), 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), April 2009 (poster)

Abstract
MR image reconstruction from undersampled k-space can be improved by nonlinear denoising estimators since they incorporate statistical prior knowledge about image sparsity. Reconstruction quality depends crucially on the undersampling design (k-space trajectory), in a manner complicated by the nonlinear and signal-dependent characteristics of these methods. We propose an algorithm to assess and optimize k-space trajectories for sparse MRI reconstruction, based on Bayesian experimental design, which is scaled up to full MR images by a novel variational relaxation to iteratively reweighted FFT or gridding computations. Designs are built sequentially by adding phase encodes predicted to be most informative, given the combination of previous measurements with image prior information.

ei

PDF Web [BibTex]

ei Seeger, M., Nickisch, H., Pohmann, R., Schölkopf, B. Optimization of k-Space Trajectories by Bayesian Experimental Design 17(2627), 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), April 2009 (poster)

PDF Web [BibTex]

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MR-Based Attenuation Correction for PET/MR

Hofmann, M., Steinke, F., Bezrukov, I., Kolb, A., Aschoff, P., Lichy, M., Erb, M., Nägele, T., Brady, M., Schölkopf, B., Pichler, B.

17(260), 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), April 2009 (poster)

Abstract
There has recently been a growing interest in combining PET and MR. Attenuation correction (AC), which accounts for radiation attenuation properties of the tissue, is mandatory for quantitative PET. In the case of PET/MR the attenuation map needs to be determined from the MR image. This is intrinsically difficult as MR intensities are not related to the electron density information of the attenuation map. Using ultra-short echo (UTE) acquisition, atlas registration and machine learning, we present methods that allow prediction of the attenuation map based on the MR image both for brain and whole body imaging.

ei

PDF Web [BibTex]

ei Hofmann, M., Steinke, F., Bezrukov, I., Kolb, A., Aschoff, P., Lichy, M., Erb, M., Nägele, T., Brady, M., Schölkopf, B., Pichler, B. MR-Based Attenuation Correction for PET/MR 17(260), 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), April 2009 (poster)

PDF Web [BibTex]

2006

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Some observations on the pedestal effect or dipper function

Henning, B., Wichmann, F.

Journal of Vision, 6(13):50, 2006 Fall Vision Meeting of the Optical Society of America, December 2006 (poster)

Abstract
The pedestal effect is the large improvement in the detectabilty of a sinusoidal “signal” grating observed when the signal is added to a masking or “pedestal” grating of the same spatial frequency, orientation, and phase. We measured the pedestal effect in both broadband and notched noise - noise from which a 1.5-octave band centred on the signal frequency had been removed. Although the pedestal effect persists in broadband noise, it almost disappears in the notched noise. Furthermore, the pedestal effect is substantial when either high- or low-pass masking noise is used. We conclude that the pedestal effect in the absence of notched noise results principally from the use of information derived from channels with peak sensitivities at spatial frequencies different from that of the signal and pedestal. The spatial-frequency components of the notched noise above and below the spatial frequency of the signal and pedestal prevent the use of information about changes in contrast carried in channels tuned to spatial frequencies that are very much different from that of the signal and pedestal. Thus the pedestal or dipper effect measured without notched noise is not a characteristic of individual spatial-frequency tuned channels.

ei

Web DOI [BibTex]

2006

ei Henning, B., Wichmann, F. Some observations on the pedestal effect or dipper function Journal of Vision, 6(13):50, 2006 Fall Vision Meeting of the Optical Society of America, December 2006 (poster)

Web DOI [BibTex]

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Optimizing Spatial Filters for BCI: Margin- and Evidence-Maximization Approaches

Farquhar, J., Hill, N., Schölkopf, B.

Challenging Brain-Computer Interfaces: MAIA Workshop 2006, pages: 1, November 2006 (poster)

Abstract
We present easy-to-use alternatives to the often-used two-stage Common Spatial Pattern + classifier approach for spatial filtering and classification of Event-Related Desychnronization signals in BCI. We report two algorithms that aim to optimize the spatial filters according to a criterion more directly related to the ability of the algorithms to generalize to unseen data. Both are based upon the idea of treating the spatial filter coefficients as hyperparameters of a kernel or covariance function. We then optimize these hyper-parameters directly along side the normal classifier parameters with respect to our chosen learning objective function. The two objectives considered are margin maximization as used in Support-Vector Machines and the evidence maximization framework used in Gaussian Processes. Our experiments assessed generalization error as a function of the number of training points used, on 9 BCI competition data sets and 5 offline motor imagery data sets measured in Tubingen. Both our approaches sho w consistent improvements relative to the commonly used CSP+linear classifier combination. Strikingly, the improvement is most significant in the higher noise cases, when either few trails are used for training, or with the most poorly performing subjects. This a reversal of the usual "rich get richer" effect in the development of CSP extensions, which tend to perform best when the signal is strong enough to accurately find their additional parameters. This makes our approach particularly suitable for clinical application where high levels of noise are to be expected.

ei

PDF PDF [BibTex]

ei Farquhar, J., Hill, N., Schölkopf, B. Optimizing Spatial Filters for BCI: Margin- and Evidence-Maximization Approaches Challenging Brain-Computer Interfaces: MAIA Workshop 2006, pages: 1, November 2006 (poster)

PDF PDF [BibTex]

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Learning Eye Movements

Kienzle, W., Wichmann, F., Schölkopf, B., Franz, M.

Sensory Coding And The Natural Environment, 2006, pages: 1, September 2006 (poster)

Abstract
The human visual system samples images through saccadic eye movements which rapidly change the point of fixation. Although the selection of eye movement targets depends on numerous top-down mechanisms, a number of recent studies have shown that low-level image features such as local contrast or edges play an important role. These studies typically used predefined image features which were afterwards experimentally verified. Here, we follow a complementary approach: instead of testing a set of candidate image features, we infer these hypotheses from the data, using methods from statistical learning. To this end, we train a non-linear classifier on fixated vs. randomly selected image patches without making any physiological assumptions. The resulting classifier can be essentially characterized by a nonlinear combination of two center-surround receptive fields. We find that the prediction performance of this simple model on our eye movement data is indistinguishable from the physiologically motivated model of Itti & Koch (2000) which is far more complex. In particular, we obtain a comparable performance without using any multi-scale representations, long-range interactions or oriented image features.

ei

Web [BibTex]

ei Kienzle, W., Wichmann, F., Schölkopf, B., Franz, M. Learning Eye Movements Sensory Coding And The Natural Environment, 2006, pages: 1, September 2006 (poster)

Web [BibTex]

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Classification of natural scenes: Critical features revisited

Drewes, J., Wichmann, F., Gegenfurtner, K.

Journal of Vision, 6(6):561, 6th Annual Meeting of the Vision Sciences Society (VSS), June 2006 (poster)

Abstract
Human observers are capable of detecting animals within novel natural scenes with remarkable speed and accuracy. Despite the seeming complexity of such decisions it has been hypothesized that a simple global image feature, the relative abundance of high spatial frequencies at certain orientations, could underly such fast image classification (A. Torralba & A. Oliva, Network: Comput. Neural Syst., 2003). We successfully used linear discriminant analysis to classify a set of 11.000 images into “animal” and “non-animal” images based on their individual amplitude spectra only (Drewes, Wichmann, Gegenfurtner VSS 2005). We proceeded to sort the images based on the performance of our classifier, retaining only the best and worst classified 400 images (“best animals”, “best distractors” and “worst animals”, “worst distractors”). We used a Go/No-go paradigm to evaluate human performance on this subset of our images. Both reaction time and proportion of correctly classified images showed a significant effect of classification difficulty. Images more easily classified by our algorithm were also classified faster and better by humans, as predicted by the Torralba & Oliva hypothesis. We then equated the amplitude spectra of the 400 images, which, by design, reduced algorithmic performance to chance whereas human performance was only slightly reduced (cf. Wichmann, Rosas, Gegenfurtner, VSS 2005). Most importantly, the same images as before were still classified better and faster, suggesting that even in the original condition features other than specifics of the amplitude spectrum made particular images easy to classify, clearly at odds with the Torralba & Oliva hypothesis.

ei

Web DOI [BibTex]

ei Drewes, J., Wichmann, F., Gegenfurtner, K. Classification of natural scenes: Critical features revisited Journal of Vision, 6(6):561, 6th Annual Meeting of the Vision Sciences Society (VSS), June 2006 (poster)

Web DOI [BibTex]

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The pedestal effect is caused by off-frequency looking, not nonlinear transduction or contrast gain-control

Wichmann, F., Henning, B.

Journal of Vision, 6(6):194, 6th Annual Meeting of the Vision Sciences Society (VSS), June 2006 (poster)

Abstract
The pedestal or dipper effect is the large improvement in the detectabilty of a sinusoidal grating observed when the signal is added to a pedestal or masking grating having the signal‘s spatial frequency, orientation, and phase. The effect is largest with pedestal contrasts just above the ‘threshold‘ in the absence of a pedestal. We measured the pedestal effect in both broadband and notched masking noise---noise from which a 1.5- octave band centered on the signal and pedestal frequency had been removed. The pedestal effect persists in broadband noise, but almost disappears with notched noise. The spatial-frequency components of the notched noise that lie above and below the spatial frequency of the signal and pedestal prevent the use of information about changes in contrast carried in channels tuned to spatial frequencies that are very much different from that of the signal and pedestal. We conclude that the pedestal effect in the absence of notched noise results principally from the use of information derived from channels with peak sensitivities at spatial frequencies that are different from that of the signal and pedestal. Thus the pedestal or dipper effect is not a characteristic of individual spatial-frequency tuned channels.

ei

Web DOI [BibTex]

ei Wichmann, F., Henning, B. The pedestal effect is caused by off-frequency looking, not nonlinear transduction or contrast gain-control Journal of Vision, 6(6):194, 6th Annual Meeting of the Vision Sciences Society (VSS), June 2006 (poster)

Web DOI [BibTex]

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The Pedestal Effect is Caused by Off-Frequency Looking, not Nonlinear Transduction or Contrast Gain-Control

Wichmann, F., Henning, G.

9, pages: 174, 9th T{\"u}bingen Perception Conference (TWK), March 2006 (poster)

Abstract
The pedestal or dipper effect is the large improvement in the detectability of a sinusoidal grating observed when the signal is added to a pedestal or masking grating having the signal‘s spatial frequency, orientation, and phase. The effect is largest with pedestal contrasts just above the ‘threshold’ in the absence of a pedestal. We measured the pedestal effect in both broadband and notched masking noise---noise from which a 1.5-octave band centered on the signal and pedestal frequency had been removed. The pedestal effect persists in broadband noise, but almost disappears with notched noise. The spatial-frequency components of the notched noise that lie above and below the spatial frequency of the signal and pedestal prevent the use of information about changes in contrast carried in channels tuned to spatial frequencies that are very much different from that of the signal and pedestal. We conclude that the pedestal effect in the absence of notched noise results principally from the use of information derived from channels with peak sensitivities at spatial frequencies that are different from that of the signal and pedestal. Thus the pedestal or dipper effect is not a characteristic of individual spatial-frequency tuned channels.

ei

Web [BibTex]

ei Wichmann, F., Henning, G. The Pedestal Effect is Caused by Off-Frequency Looking, not Nonlinear Transduction or Contrast Gain-Control 9, pages: 174, 9th T{\"u}bingen Perception Conference (TWK), March 2006 (poster)

Web [BibTex]

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Classification of Natural Scenes: Critical Features Revisited

Drewes, J., Wichmann, F., Gegenfurtner, K.

9, pages: 92, 9th T{\"u}bingen Perception Conference (TWK), March 2006 (poster)

Abstract
Human observers are capable of detecting animals within novel natural scenes with remarkable speed and accuracy. Despite the seeming complexity of such decisions it has been hypothesized that a simple global image feature, the relative abundance of high spatial frequencies at certain orientations, could underly such fast image classification [1]. We successfully used linear discriminant analysis to classify a set of 11.000 images into “animal” and “non-animal” images based on their individual amplitude spectra only [2]. We proceeded to sort the images based on the performance of our classifier, retaining only the best and worst classified 400 images ("best animals", "best distractors" and "worst animals", "worst distractors"). We used a Go/No-go paradigm to evaluate human performance on this subset of our images. Both reaction time and proportion of correctly classified images showed a significant effect of classification difficulty. Images more easily classified by our algorithm were also classified faster and better by humans, as predicted by the Torralba & Oliva hypothesis. We then equated the amplitude spectra of the 400 images, which, by design, reduced algorithmic performance to chance whereas human performance was only slightly reduced [3]. Most importantly, the same images as before were still classified better and faster, suggesting that even in the original condition features other than specifics of the amplitude spectrum made particular images easy to classify, clearly at odds with the Torralba & Oliva hypothesis.

ei

Web [BibTex]

ei Drewes, J., Wichmann, F., Gegenfurtner, K. Classification of Natural Scenes: Critical Features Revisited 9, pages: 92, 9th T{\"u}bingen Perception Conference (TWK), March 2006 (poster)

Web [BibTex]

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Factorial Coding of Natural Images: How Effective are Linear Models in Removing Higher-Order Dependencies?

Bethge, M.

9, pages: 90, 9th T{\"u}bingen Perception Conference (TWK), March 2006 (poster)

Abstract
The performance of unsupervised learning models for natural images is evaluated quantitatively by means of information theory. We estimate the gain in statistical independence (the multi-information reduction) achieved with independent component analysis (ICA), principal component analysis (PCA), zero-phase whitening, and predictive coding. Predictive coding is translated into the transform coding framework, where it can be characterized by the constraint of a triangular filter matrix. A randomly sampled whitening basis and the Haar wavelet are included into the comparison as well. The comparison of all these methods is carried out for different patch sizes, ranging from 2x2 to 16x16 pixels. In spite of large differences in the shape of the basis functions, we find only small differences in the multi-information between all decorrelation transforms (5% or less) for all patch sizes. Among the second-order methods, PCA is optimal for small patch sizes and predictive coding performs best for large patch sizes. The extra gain achieved with ICA is always less than 2%. In conclusion, the `edge filters‘ found with ICA lead only to a surprisingly small improvement in terms of its actual objective.

ei

Web [BibTex]

ei Bethge, M. Factorial Coding of Natural Images: How Effective are Linear Models in Removing Higher-Order Dependencies? 9, pages: 90, 9th T{\"u}bingen Perception Conference (TWK), March 2006 (poster)

Web [BibTex]

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Classification of natural scenes: critical features revisited

Drewes, J., Wichmann, F., Gegenfurtner, K.

Experimentelle Psychologie: Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen, 48, pages: 251, 2006 (poster)

ei

[BibTex]

ei Drewes, J., Wichmann, F., Gegenfurtner, K. Classification of natural scenes: critical features revisited Experimentelle Psychologie: Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen, 48, pages: 251, 2006 (poster)

[BibTex]

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Texture and haptic cues in slant discrimination: combination is sensitive to reliability but not statistically optimal

Rosas, P., Wagemans, J., Ernst, M., Wichmann, F.

Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen (TeaP 2006), 48, pages: 80, 2006 (poster)

ei

[BibTex]

ei Rosas, P., Wagemans, J., Ernst, M., Wichmann, F. Texture and haptic cues in slant discrimination: combination is sensitive to reliability but not statistically optimal Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen (TeaP 2006), 48, pages: 80, 2006 (poster)

[BibTex]

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Ähnlichkeitsmasse in Modellen zur Kategorienbildung

Jäkel, F., Wichmann, F.

Experimentelle Psychologie: Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen, 48, pages: 223, 2006 (poster)

ei

[BibTex]

ei Jäkel, F., Wichmann, F. Ähnlichkeitsmasse in Modellen zur Kategorienbildung Experimentelle Psychologie: Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen, 48, pages: 223, 2006 (poster)

[BibTex]

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The pedestal effect is caused by off-frequency looking, not nonlinear transduction or contrast gain-control

Wichmann, F., Henning, B.

Experimentelle Psychologie: Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen, 48, pages: 205, 2006 (poster)

ei

[BibTex]

ei Wichmann, F., Henning, B. The pedestal effect is caused by off-frequency looking, not nonlinear transduction or contrast gain-control Experimentelle Psychologie: Beitr{\"a}ge zur 48. Tagung experimentell arbeitender Psychologen, 48, pages: 205, 2006 (poster)

[BibTex]