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Search Results: 1 - 10 of 119475 matches for " T. Friedrich "
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Information transmission in oscillatory neural activity
Kilian Koepsell,Friedrich T. Sommer
Mathematics , 2008, DOI: 10.1007/s00422-008-0273-6
Abstract: Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.
Zuordnung der Schmerzlokalisation bei monosegmentaler Wurzelirritation in der unteren Lendenwirbels ule
Machacek P,Cermak T,Friedrich M
Journal für Mineralstoffwechsel , 2007,
Abstract: Studienziel: Ziel dieser Studie ist es, zu kl ren, wie zuverl ssig die in der Literatur angegebenen klassischen Dermatommodelle (Darstellung der Schmerzausstrahlung bei L sion einzelner Nervenwurzeln) den entsprechenden Segmenten der Lendenwirbels ule zugeordnet werden k nnen. Methode: Es werden eigene Ergebnisse und externe Studien, die sich mit bandscheibenbedingten Schmerzprojektionen besch ftigen, verglichen. Die Literatursuche erfolgt EDV-unterstützt. Ergebnisse: Bezüglich der Dermatomverl ufe im Bereich der unteren LWS gibt es keine eindeutigen übereinstimmungen. Es besteht ein Widerspruch zwischen der am h ufigsten auftretenden Schmerzprojektion (S1) und dem am h ufigsten operierten Segment (L4/L5). Schlu folgerung: Trotz wissenschaftlich fundierter Modelle ist die Schmerzausstrahlung gegenüber den klassischen Dermatommodellen ein nur bedingt geeigneter Parameter zur Segmentdefinition.
Learning and exploration in action-perception loops
Daniel Y. Little,Friedrich T. Sommer
Frontiers in Neural Circuits , 2013, DOI: 10.3389/fncir.2013.00037
Abstract: Discovering the structure underlying observed data is a recurring problem in machine learning with important applications in neuroscience. It is also a primary function of the brain. When data can be actively collected in the context of a closed action-perception loop, behavior becomes a critical determinant of learning efficiency. Psychologists studying exploration and curiosity in humans and animals have long argued that learning itself is a primary motivator of behavior. However, the theoretical basis of learning-driven behavior is not well understood. Previous computational studies of behavior have largely focused on the control problem of maximizing acquisition of rewards and have treated learning the structure of data as a secondary objective. Here, we study exploration in the absence of external reward feedback. Instead, we take the quality of an agent's learned internal model to be the primary objective. In a simple probabilistic framework, we derive a Bayesian estimate for the amount of information about the environment an agent can expect to receive by taking an action, a measure we term the predicted information gain (PIG). We develop exploration strategies that approximately maximize PIG. One strategy based on value-iteration consistently learns faster than previously developed reward-free exploration strategies across a diverse range of environments. Psychologists believe the evolutionary advantage of learning-driven exploration lies in the generalized utility of an accurate internal model. Consistent with this hypothesis, we demonstrate that agents which learn more efficiently during exploration are later better able to accomplish a range of goal-directed tasks. We will conclude by discussing how our work elucidates the explorative behaviors of animals and humans, its relationship to other computational models of behavior, and its potential application to experimental design, such as in closed-loop neurophysiology studies.
Learning in embodied action-perception loops through exploration
Daniel Y. Little,Friedrich T. Sommer
Computer Science , 2011,
Abstract: Although exploratory behaviors are ubiquitous in the animal kingdom, their computational underpinnings are still largely unknown. Behavioral Psychology has identified learning as a primary drive underlying many exploratory behaviors. Exploration is seen as a means for an animal to gather sensory data useful for reducing its ignorance about the environment. While related problems have been addressed in Data Mining and Reinforcement Learning, the computational modeling of learning-driven exploration by embodied agents is largely unrepresented. Here, we propose a computational theory for learning-driven exploration based on the concept of missing information that allows an agent to identify informative actions using Bayesian inference. We demonstrate that when embodiment constraints are high, agents must actively coordinate their actions to learn efficiently. Compared to earlier approaches, our exploration policy yields more efficient learning across a range of worlds with diverse structures. The improved learning in turn affords greater success in general tasks including navigation and reward gathering. We conclude by discussing how the proposed theory relates to previous information-theoretic objectives of behavior, such as predictive information and the free energy principle, and how it might contribute to a general theory of exploratory behavior.
When can dictionary learning uniquely recover sparse data from subsamples?
Christopher J. Hillar,Friedrich T. Sommer
Quantitative Biology , 2011,
Abstract: Sparse coding or sparse dictionary learning has been widely used to recover underlying structure in many kinds of natural data. Here, we provide conditions guaranteeing when this recovery is universal; that is, when sparse codes and dictionaries are unique (up to natural symmetries). Our main tool is a useful lemma in combinatorial matrix theory that allows us to derive bounds on the sample sizes guaranteeing such uniqueness under various assumptions for how training data are generated. Whenever the conditions to one of our theorems are met, any sparsity-constrained learning algorithm that succeeds in reconstructing the data recovers the original sparse codes and dictionary. We also discuss potential applications to neuroscience and data analysis.
Estimating mixed layer nitrate in the North Atlantic Ocean
T. Steinhoff,T. Friedrich,S. E. Hartman,A. Oschlies
Biogeosciences Discussions , 2009,
Abstract: Here we present an equation for the estimation of nitrate in surface waters of the North Atlantic Ocean (40° N to 52° N, 10° W to 60° W). The equation was derived by multiple linear regression (MLR) from nitrate, sea surface temperature (SST) observational data and model mixed layer depth (MLD) data. The observational data were taken from merchant vessels that have crossed the North Atlantic on a regular basis in 2002/2003 and from 2005 to present. It is important to find a robust and realistic esitmate of MLD because the deepening of the mixed layer is crucial for nitrate supply to the surface. We compared model data from two models (FOAM and Mercator) with MLD derived from float data (using various criteria). The Mercator model gives a MLD estimate that is close to the MLD derived from floats. MLR was established using SST, MLD from Mercator, time and latitude as predictors. Additionally a neural network was trained with the same dataset and the results were validated against both model data as a "ground truth" and an independent observational dataset. This validation produced RMS errors of the same order for MLR and the neural network approach. We conclude that it is possible to estimate nitrate concentrations with an uncertainty of ±1.5 μmol L 1 in the North Atlantic.
High speed coding for velocity by archerfish retinal ganglion cells
Viola Kretschmer, Friedrich Kretschmer, Malte T Ahlers, Josef Ammermüller
BMC Neuroscience , 2012, DOI: 10.1186/1471-2202-13-69
Abstract: We compared stimulus reconstruction quality based on the ganglion cell response parameters latency, first interspike interval, and rate. For stimulus reconstruction of moving stimuli using latency was superior to using the other stimulus parameters. This was true for absolute latency, with respect to stimulus onset, as well as for relative latency, with respect to population response onset. Iteratively increasing the number of cells used for reconstruction decreased the calculated error close to zero.Latency is the fastest response parameter available to the brain. Therefore, latency coding is best suited for high speed coding of moving objects. The quantitative data of this study are in good accordance with previously published behavioural response latencies.
Internally generated millennial-scale climate variability in an earth system model of intermediate complexity: sensitivity to ocean bathymetry and orbital forcing
T. Friedrich,A. Timmermann,L. Menviel,O. Timm
Geoscientific Model Development Discussions , 2010,
Abstract: The effect of orbital variations on simulated millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) is studied using the earth system model of intermediate complexity LOVECLIM. It is found that for present-day topographic boundary conditions low obliquity values (~22.1°) favor the triggering of internally generated millennial-scale variability in the North Atlantic region. Reducing the obliquity leads to changes of the pause-pulse ratio of the corresponding AMOC oscillations. Stochastic excitations of the density-driven overturning circulation in the Nordic Seas can create regional sea-ice anomalies and a subsequent reorganization of the atmospheric circulation. The resulting remote atmospheric anomalies over the Hudson Bay can release freshwater pulses into the Labrador Sea leading to a subsequent reduction of convective activity. The millennial-scale AMOC oscillations disappear if LGM bathymetry (with closed Hudson Bay) or Hudson Bay salinity is prescribed. Furthermore, our study documents the marine and terrestrial carbon cycle response to millennial-scale AMOC variability.
Endocardial microwave ablation in patients following mitral valve surgery
Michael Knaut,T. Link,Friedrich Jung,Stefan Brose
Applied Cardiopulmonary Pathophysiology , 2012,
Abstract: Atrial fibrillation not only impairs the quality of life in patients, it is also associated with higher mortality and morbidity caused by embolic events or therapeutic anticoagulation treatment. The present prospective registry study evaluated the conversion rates and the influencing factors on outcomes of mitral valve surgery and concomitant microwave ablation in 191 patients with permanent atrial fibrillation. Approximately 60% of the patients remained in sinus rhythm during the postoperative period whereas, depending on the study data, conversion rates between 4% and 33.5% have been reported after cardiac surgery alone without additional surgical rhythm control. Significant influencing factors on postoperative sinus rhythm were the presence of diabetes mellitus or a history of myocardial infarction, the preoperative atrial size, and tendentially, surgery duration. There were no ablation-related complications. During the 1.5-year follow-up it became clear that prolonged surgery duration (in most cases due to operative complexity with greater risk) and postoperative recurrence of atrial fibrillation were significant factors influencing mortality.
Convergence of EU-Regions. A Literature Report
Hans-Friedrich-Eckey,Matthias Türck
Investigaciones Regionales , 2007,
Abstract: The main focus of convergence studies surrounds the question ofwhether poor economies catch up to wealthier economies over time. The regionalconvergence process in Europe has generated considerable interest in recent years.Due to financial straits regional convergence is a central question, since importantfunds aim at diminishing disparities. There are many studies published recently dealingwith this issue using different empirical approaches. The β-convergence framework,which was introduced by Barro and Sala-i-Martin, is, for instance, an oftenused approach. This paper provides a critical review of the used approaches and summarisesthe results. A special problem is that authors refer to different periods andMember State groups (EU-9, EU-15, etc.). Altogether it can be stated that most modelsfind a slow convergence process. In particular, the increase of regional inequalitiescaused by the enlargement of the EU with the New Member States from Centraland Eastern Europe explains the existence of convergence clubs.
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