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2014


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MoSh: Motion and Shape Capture from Sparse Markers

Loper, M. M., Mahmood, N., Black, M. J.

ACM Transactions on Graphics, (Proc. SIGGRAPH Asia), 33(6):220:1-220:13, ACM, New York, NY, USA, November 2014 (article)

Abstract
Marker-based motion capture (mocap) is widely criticized as producing lifeless animations. We argue that important information about body surface motion is present in standard marker sets but is lost in extracting a skeleton. We demonstrate a new approach called MoSh (Motion and Shape capture), that automatically extracts this detail from mocap data. MoSh estimates body shape and pose together using sparse marker data by exploiting a parametric model of the human body. In contrast to previous work, MoSh solves for the marker locations relative to the body and estimates accurate body shape directly from the markers without the use of 3D scans; this effectively turns a mocap system into an approximate body scanner. MoSh is able to capture soft tissue motions directly from markers by allowing body shape to vary over time. We evaluate the effect of different marker sets on pose and shape accuracy and propose a new sparse marker set for capturing soft-tissue motion. We illustrate MoSh by recovering body shape, pose, and soft-tissue motion from archival mocap data and using this to produce animations with subtlety and realism. We also show soft-tissue motion retargeting to new characters and show how to magnify the 3D deformations of soft tissue to create animations with appealing exaggerations.

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pdf video data pdf from publisher link (url) DOI Project Page Project Page Project Page [BibTex]

2014


pdf video data pdf from publisher link (url) DOI Project Page Project Page Project Page [BibTex]


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Can I recognize my body’s weight? The influence of shape and texture on the perception of self

Piryankova, I., Stefanucci, J., Romero, J., de la Rosa, S., Black, M., Mohler, B.

ACM Transactions on Applied Perception for the Symposium on Applied Perception, 11(3):13:1-13:18, September 2014 (article)

Abstract
The goal of this research was to investigate women’s sensitivity to changes in their perceived weight by altering the body mass index (BMI) of the participants’ personalized avatars displayed on a large-screen immersive display. We created the personalized avatars with a full-body 3D scanner that records both the participants’ body geometry and texture. We altered the weight of the personalized avatars to produce changes in BMI while keeping height, arm length and inseam fixed and exploited the correlation between body geometry and anthropometric measurements encapsulated in a statistical body shape model created from thousands of body scans. In a 2x2 psychophysical experiment, we investigated the relative importance of visual cues, namely shape (own shape vs. an average female body shape with equivalent height and BMI to the participant) and texture (own photo-realistic texture or checkerboard pattern texture) on the ability to accurately perceive own current body weight (by asking them ‘Is the avatar the same weight as you?’). Our results indicate that shape (where height and BMI are fixed) had little effect on the perception of body weight. Interestingly, the participants perceived their body weight veridically when they saw their own photo-realistic texture and significantly underestimated their body weight when the avatar had a checkerboard patterned texture. The range that the participants accepted as their own current weight was approximately a 0.83 to −6.05 BMI% change tolerance range around their perceived weight. Both the shape and the texture had an effect on the reported similarity of the body parts and the whole avatar to the participant’s body. This work has implications for new measures for patients with body image disorders, as well as researchers interested in creating personalized avatars for games, training applications or virtual reality.

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pdf DOI Project Page Project Page [BibTex]

pdf DOI Project Page Project Page [BibTex]


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Breathing Life into Shape: Capturing, Modeling and Animating 3D Human Breathing

Tsoli, A., Mahmood, N., Black, M. J.

ACM Transactions on Graphics, (Proc. SIGGRAPH), 33(4):52:1-52:11, ACM, New York, NY, July 2014 (article)

Abstract
Modeling how the human body deforms during breathing is important for the realistic animation of lifelike 3D avatars. We learn a model of body shape deformations due to breathing for different breathing types and provide simple animation controls to render lifelike breathing regardless of body shape. We capture and align high-resolution 3D scans of 58 human subjects. We compute deviations from each subject’s mean shape during breathing, and study the statistics of such shape changes for different genders, body shapes, and breathing types. We use the volume of the registered scans as a proxy for lung volume and learn a novel non-linear model relating volume and breathing type to 3D shape deformations and pose changes. We then augment a SCAPE body model so that body shape is determined by identity, pose, and the parameters of the breathing model. These parameters provide an intuitive interface with which animators can synthesize 3D human avatars with realistic breathing motions. We also develop a novel interface for animating breathing using a spirometer, which measures the changes in breathing volume of a “breath actor.”

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pdf video link (url) DOI Project Page Project Page Project Page [BibTex]


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3D Traffic Scene Understanding from Movable Platforms

Geiger, A., Lauer, M., Wojek, C., Stiller, C., Urtasun, R.

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 36(5):1012-1025, published, IEEE, Los Alamitos, CA, May 2014 (article)

Abstract
In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow and occupancy grids. For each of these cues we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

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pdf link (url) [BibTex]

pdf link (url) [BibTex]


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Adaptive Offset Correction for Intracortical Brain Computer Interfaces

Homer, M. L., Perge, J. A., Black, M. J., Harrison, M. T., Cash, S. S., Hochberg, L. R.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 22(2):239-248, March 2014 (article)

Abstract
Intracortical brain computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user’s ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called MOCA, was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ± 10.1\%; p < 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs.

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pdf DOI Project Page [BibTex]

pdf DOI Project Page [BibTex]


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Juggling revisited — A voxel based morphometry study with expert jugglers

Gerber, P., Schlaffke, L., Heba, S., Greenlee, M., Schultz, T., Schmidt-Wilcke, T.

NeuroImage, 95, pages: 320-325, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Assessing attention and cognitive function in completely locked-in state with event-related brain potentials and epidural electrocorticography

Bensch, M., Martens, S., Halder, S., Hill, J., Nijboer, F., Ramos, A., Birbaumer, N., Bodgan, M., Kotchoubey, B., Rosenstiel, W., Schölkopf, B., Gharabaghi, A.

Journal of Neural Engineering, 11(2):026006, 2014 (article)

Abstract
Objective. Patients in the completely locked-in state (CLIS), due to, for example, amyotrophic lateral sclerosis (ALS), no longer possess voluntary muscle control. Assessing attention and cognitive function in these patients during the course of the disease is a challenging but essential task for both nursing staff and physicians. Approach. An electrophysiological cognition test battery, including auditory and semantic stimuli, was applied in a late-stage ALS patient at four different time points during a six-month epidural electrocorticography (ECoG) recording period. Event-related cortical potentials (ERP), together with changes in the ECoG signal spectrum, were recorded via 128 channels that partially covered the left frontal, temporal and parietal cortex. Main results. Auditory but not semantic stimuli induced significant and reproducible ERP projecting to specific temporal and parietal cortical areas. N1/P2 responses could be detected throughout the whole study period. The highest P3 ERP was measured immediately after the patient's last communication through voluntary muscle control, which was paralleled by low theta and high gamma spectral power. Three months after the patient's last communication, i.e., in the CLIS, P3 responses could no longer be detected. At the same time, increased activity in low-frequency bands and a sharp drop of gamma spectral power were recorded. Significance. Cortical electrophysiological measures indicate at least partially intact attention and cognitive function during sparse volitional motor control for communication. Although the P3 ERP and frequency-specific changes in the ECoG spectrum may serve as indicators for CLIS, a close-meshed monitoring will be required to define the exact time point of the transition.

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DOI [BibTex]

DOI [BibTex]


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Identifiability of Gaussian Structural Equation Models with Equal Error Variances

Peters, J., Bühlman, P.

Biometrika, 101(1):219-228, 2014 (article)

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DOI [BibTex]


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Quantifying the effect of intertrial dependence on perceptual decisions

Fründ, I., Wichmann, F., Macke, J.

Journal of Vision, 14(7):1-16, 2014 (article)

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Web PDF link (url) DOI [BibTex]

Web PDF link (url) DOI [BibTex]


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Two numerical models designed to reproduce Saturn ring temperatures as measured by Cassini-CIRS

Altobelli, N., Lopez-Paz, D., Pilorz, S., Spilker, L., Morishima, R., Brooks, S., Leyrat, C., Deau, E., Edgington, S., Flandes, A.

Icarus, 238(0):205 - 220, 2014 (article)

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Web link (url) DOI [BibTex]

Web link (url) DOI [BibTex]


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CAM: Causal Additive Models, high-dimensional order search and penalized regression

Bühlmann, P., Peters, J., Ernest, J.

Annals of Statistics, 42(6):2526-2556, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Unsupervised identification of neural events in local field potentials

Besserve, M., Schölkopf, B., Logothetis, N. K.

44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

ei

[BibTex]

[BibTex]


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Policy Evaluation with Temporal Differences: A Survey and Comparison

Dann, C., Neumann, G., Peters, J.

Journal of Machine Learning Research, 15, pages: 809-883, 2014 (article)

ei

PDF [BibTex]

PDF [BibTex]


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Uncovering the Structure and Temporal Dynamics of Information Propagation

Gomez Rodriguez, M., Leskovec, J., Balduzzi, D., Schölkopf, B.

Network Science, 2(1):26-65, 2014 (article)

Abstract
Time plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion—when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on-going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.

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DOI [BibTex]


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Causal discovery via reproducing kernel Hilbert space embeddings

Chen, Z., Zhang, K., Chan, L., Schölkopf, B.

Neural Computation, 26(7):1484-1517, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Impact of Large-Scale Climate Extremes on Biospheric Carbon Fluxes: An Intercomparison Based on MsTMIP Data

Zscheischler, J., Michalak, A., Schwalm, M., Mahecha, M., Huntzinger, D., Reichstein, M., Berthier, G., Ciais, P., Cook, R., El-Masri, B., Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W., Wei, Y., Yang, J., Zeng, N.

Global Biogeochemical Cycles, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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A Brain-Computer Interface Based on Self-Regulation of Gamma-Oscillations in the Superior Parietal Cortex

Grosse-Wentrup, M., Schölkopf, B.

Journal of Neural Engineering, 11(5):056015, 2014 (article)

Abstract
Objective. Brain–computer interface (BCI) systems are often based on motor- and/or sensory processes that are known to be impaired in late stages of amyotrophic lateral sclerosis (ALS). We propose a novel BCI designed for patients in late stages of ALS that only requires high-level cognitive processes to transmit information from the user to the BCI. Approach. We trained subjects via EEG-based neurofeedback to self-regulate the amplitude of gamma-oscillations in the superior parietal cortex (SPC). We argue that parietal gamma-oscillations are likely to be associated with high-level attentional processes, thereby providing a communication channel that does not rely on the integrity of sensory- and/or motor-pathways impaired in late stages of ALS. Main results. Healthy subjects quickly learned to self-regulate gamma-power in the SPC by alternating between states of focused attention and relaxed wakefulness, resulting in an average decoding accuracy of 70.2%. One locked-in ALS patient (ALS-FRS-R score of zero) achieved an average decoding accuracy significantly above chance-level though insufficient for communication (55.8%). Significance. Self-regulation of gamma-power in the SPC is a feasible paradigm for brain–computer interfacing and may be preserved in late stages of ALS. This provides a novel approach to testing whether completely locked-in ALS patients retain the capacity for goal-directed thinking.

ei

Web DOI [BibTex]


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On power law distributions in large-scale taxonomies

Babbar, R., Metzig, C., Partalas, I., Gaussier, E., Amini, M.

SIGKDD Explorations, Special Issue on Big Data, 16(1):47-56, 2014 (article)

ei

[BibTex]

[BibTex]


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Quantifying statistical dependency

Besserve, M.

Research Network on Learning Systems Summer School, 2014 (talk)

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[BibTex]

[BibTex]


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Predicting Motor Learning Performance from Electroencephalographic Data

Meyer, T., Peters, J., Zander, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of NeuroEngineering and Rehabilitation, 11:24, 2014 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Special issue on autonomous grasping and manipulation

Ben Amor, H., Saxena, A., Hudson, N., Peters, J.

Autonomous Robots, 36(1-2):1-3, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Evaluation of Positron Emission Tomographic Tracers for Imaging of Papillomavirus-Induced Tumors in Rabbits

Probst, S., Wiehr, S., Mantlik, F., Schmidt, H., Kolb, A., Münch, P., Delcuratolo, M., Stubenrauch, F., Pichler, B., Iftner, T.

Molecular Imaging, 13(1):1536-0121, 2014 (article)

ei

Web [BibTex]

Web [BibTex]


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Extreme events in gross primary production: a characterization across continents

Zscheischler, J., Reichstein, M., Harmeling, S., Rammig, A., Tomelleri, E., Mahecha, M.

Biogeosciences, 11, pages: 2909-2924, 2014 (article)

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PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Single-Source Domain Adaptation with Target and Conditional Shift

Zhang, K., Schölkopf, B., Muandet, K., Wang, Z., Zhou, Z., Persello, C.

In Regularization, Optimization, Kernels, and Support Vector Machines, pages: 427-456, 19, Chapman & Hall/CRC Machine Learning & Pattern Recognition, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), Chapman and Hall/CRC, Boca Raton, USA, 2014 (inbook)

ei

[BibTex]

[BibTex]


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Indirect Robot Model Learning for Tracking Control

Bocsi, B., Csató, L., Peters, J.

Advanced Robotics, 28(9):589-599, 2014 (article)

ei

PDF DOI [BibTex]


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An extended approach for spatiotemporal gapfilling: dealing with large and systematic gaps in geoscientific datasets

v Buttlar, J., Zscheischler, J., Mahecha, M.

Nonlinear Processes in Geophysics, 21(1):203-215, 2014 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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On the Quantification Accuracy, Homogeneity, and Stability of Simultaneous Positron Emission Tomography/Magnetic Resonance Imaging Systems

Schmidt, H., Schwenzer, N., Bezrukov, I., Mantlik, F., Kolb, A., Kupferschläger, J., Pichler, B.

Investigative Radiology, 49(6):373-381, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Natural Evolution Strategies

Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J., Schmidhuber, J.

Journal of Machine Learning Research, 15, pages: 949-980, 2014 (article)

ei

PDF [BibTex]

PDF [BibTex]


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Higher-Order Tensors in Diffusion Imaging

Schultz, T., Fuster, A., Ghosh, A., Deriche, R., Florack, L., Lim, L.

In Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data, pages: 129-161, Mathematics + Visualization, (Editors: Westin, C.-F., Vilanova, A. and Burgeth, B.), Springer, 2014 (inbook)

ei

[BibTex]

[BibTex]


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Factors controlling decomposition rates of fine root litter in temperate forests and grasslands

Solly, E., Schöning, I., Boch, S., Kandeler, E., Marhan, S., Michalzik, B., Müller, J., Zscheischler, J., Trumbore, S., Schrumpf, M.

Plant and Soil, 2014 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Causal Discovery with Continuous Additive Noise Models

Peters, J., Mooij, J., Janzing, D., Schölkopf, B.

Journal of Machine Learning Research, 15, pages: 2009-2053, 2014 (article)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Fuzzy Fibers: Uncertainty in dMRI Tractography

Schultz, T., Vilanova, A., Brecheisen, R., Kindlmann, G.

In Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization, pages: 79-92, 8, Mathematics + Visualization, (Editors: Hansen, C. D., Chen, M., Johnson, C. R., Kaufman, A. E. and Hagen, H.), Springer, 2014 (inbook)

ei

[BibTex]

[BibTex]


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A few extreme events dominate global interannual variability in gross primary production

Zscheischler, J., Mahecha, M., v Buttlar, J., Harmeling, S., Jung, M., Rammig, A., Randerson, J., Schölkopf, B., Seneviratne, S., Tomelleri, E., Zaehle, S., Reichstein, M.

Environmental Research Letters, 9(3):035001, 2014 (article)

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Kernel methods in system identification, machine learning and function estimation: A survey

Pillonetto, G., Dinuzzo, F., Chen, T., De Nicolao, G., Ljung, L.

Automatica, 50(3):657-682, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Development of a novel depth of interaction PET detector using highly multiplexed G-APD cross-strip encoding

Kolb, A., Parl, C., Mantlik, F., Liu, C., Lorenz, E., Renker, D., Pichler, B.

Medical Physics, 41(8), 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Epidural electrocorticography for monitoring of arousal in locked-in state

Martens, S., Bensch, M., Halder, S., Hill, J., Nijboer, F., Ramos-Murguialday, A., Schölkopf, B., Birbaumer, N., Gharabaghi, A.

Frontiers in Human Neuroscience, 8(861), 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Nonconvex Proximal Splitting with Computational Errors

Sra, S.

In Regularization, Optimization, Kernels, and Support Vector Machines, pages: 83-102, 4, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), CRC Press, 2014 (inbook)

ei

[BibTex]

[BibTex]


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Simultaneous Whole-Body PET/MR Imaging in Comparison to PET/CT in Pediatric Oncology: Initial Results

Schäfer, J. F., Gatidis, S., Schmidt, H., Gückel, B., Bezrukov, I., Pfannenberg, C. A., Reimold, M., M., E., Fuchs, J., Claussen, C. D., Schwenzer, N. F.

Radiology, 273(1):220-231, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification

Persello, C., Boularias, A., Dalponte, M., Gobakken, T., Naesset, E., Schölkopf, B.

IEEE Transactions on Geoscience and Remote Sensing, 10(52):6652 - 6664, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Principles of PET/MR Imaging

Disselhorst, J. A., Bezrukov, I., Kolb, A., Parl, C., Pichler, B. J.

Journal of Nuclear Medicine, 55(6, Supplement 2):2S-10S, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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IM3SHAPE: Maximum likelihood galaxy shear measurement code for cosmic gravitational lensing

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

Astrophysics Source Code Library, 1, pages: 09013, 2014 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


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Efficient nearest neighbors via robust sparse hashing

Cherian, A., Sra, S., Morellas, V., Papanikolopoulos, N.

IEEE Transactions on Image Processing, 23(8):3646-3655, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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A freely-moving monkey treadmill model

Foster, J., Nuyujukian, P., Freifeld, O., Gao, H., Walker, R., Ryu, S., Meng, T., Murmann, B., Black, M., Shenoy, K.

J. of Neural Engineering, 11(4):046020, 2014 (article)

Abstract
Objective: Motor neuroscience and brain-machine interface (BMI) design is based on examining how the brain controls voluntary movement, typically by recording neural activity and behavior from animal models. Recording technologies used with these animal models have traditionally limited the range of behaviors that can be studied, and thus the generality of science and engineering research. We aim to design a freely-moving animal model using neural and behavioral recording technologies that do not constrain movement. Approach: We have established a freely-moving rhesus monkey model employing technology that transmits neural activity from an intracortical array using a head-mounted device and records behavior through computer vision using markerless motion capture. We demonstrate the excitability and utility of this new monkey model, including the fi rst recordings from motor cortex while rhesus monkeys walk quadrupedally on a treadmill. Main results: Using this monkey model, we show that multi-unit threshold-crossing neural activity encodes the phase of walking and that the average ring rate of the threshold crossings covaries with the speed of individual steps. On a population level, we find that neural state-space trajectories of walking at diff erent speeds have similar rotational dynamics in some dimensions that evolve at the step rate of walking, yet robustly separate by speed in other state-space dimensions. Significance: Freely-moving animal models may allow neuroscientists to examine a wider range of behaviors and can provide a flexible experimental paradigm for examining the neural mechanisms that underlie movement generation across behaviors and environments. For BMIs, freely-moving animal models have the potential to aid prosthetic design by examining how neural encoding changes with posture, environment, and other real-world context changes. Understanding this new realm of behavior in more naturalistic settings is essential for overall progress of basic motor neuroscience and for the successful translation of BMIs to people with paralysis.

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pdf Supplementary DOI Project Page [BibTex]

pdf Supplementary DOI Project Page [BibTex]


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Sérsic galaxy models in weak lensing shape measurement: model bias, noise bias and their interaction

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

Monthly Notices of the Royal Astronomical Society, 441(3):2528-2538, Oxford University Press, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Diminished White Matter Integrity in Patients with Systemic Lupus Erythematosus

Schmidt-Wilcke, T., Cagnoli, P., Wang, P., Schultz, T., Lotz, A., Mccune, W. J., Sundgren, P. C.

NeuroImage: Clinical, 5, pages: 291-297, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Information-Theoretic Bounded Rationality and ϵ-Optimality

Braun, DA, Ortega, PA

Entropy, 16(8):4662-4676, August 2014 (article)

Abstract
Bounded rationality concerns the study of decision makers with limited information processing resources. Previously, the free energy difference functional has been suggested to model bounded rational decision making, as it provides a natural trade-off between an energy or utility function that is to be optimized and information processing costs that are measured by entropic search costs. The main question of this article is how the information-theoretic free energy model relates to simple \(\epsilon\)-optimality models of bounded rational decision making, where the decision maker is satisfied with any action in an \(\epsilon\)-neighborhood of the optimal utility. We find that the stochastic policies that optimize the free energy trade-off comply with the notion of \(\epsilon\)-optimality. Moreover, this optimality criterion even holds when the environment is adversarial. We conclude that the study of bounded rationality based on \(\epsilon\)-optimality criteria that abstract away from the particulars of the information processing constraints is compatible with the information-theoretic free energy model of bounded rationality.

ei

DOI [BibTex]

DOI [BibTex]