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  • 1.
    Spühler, Jeannette H.
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hoffman, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    3D Fluid-Structure Interaction Simulation of Aortic Valves Using a Unified Continuum ALE FEM Model2018In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 363Article in journal (Refereed)
    Abstract [en]

    Due to advances in medical imaging, computational fluid dynamics algorithms and high performance computing, computer simulation is developing into an important tool for understanding the relationship between cardiovascular diseases and intraventricular blood flow. The field of cardiac flow simulation is challenging and highly interdisciplinary. We apply a computational framework for automated solutions of partial differential equations using Finite Element Methods where any mathematical description directly can be translated to code. This allows us to develop a cardiac model where specific properties of the heart such as fluid-structure interaction of the aortic valve can be added in a modular way without extensive efforts. In previous work, we simulated the blood flow in the left ventricle of the heart. In this paper, we extend this model by placing prototypes of both a native and a mechanical aortic valve in the outflow region of the left ventricle. Numerical simulation of the blood flow in the vicinity of the valve offers the possibility to improve the treatment of aortic valve diseases as aortic stenosis (narrowing of the valve opening) or regurgitation (leaking) and to optimize the design of prosthetic heart valves in a controlled and specific way. The fluid-structure interaction and contact problem are formulated in a unified continuum model using the conservation laws for mass and momentum and a phase function. The discretization is based on an Arbitrary Lagrangian-Eulerian space-time finite element method with streamline diffusion stabilization, and it is implemented in the open source software Unicorn which shows near optimal scaling up to thousands of cores. Computational results are presented to demonstrate the capability of our framework.

  • 2.
    Hoffman, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Vilela de Abreu, Rodrigo
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Johnson, Claes
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Computability and Adaptivity in CFD2018In: Encyclopedia of Computational Mechanics / [ed] Erwin Stein and René de Borst and Thomas J. R. Hughes, John Wiley & Sons, 2018, 2Chapter in book (Refereed)
  • 3.
    Gao, Chen-Yi
    et al.
    Chinese Acad Sci, Inst Theoret Phys, Key Lab Theoret Phys, Beijing 100190, Peoples R China.;Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China..
    Zhou, Hai-Jun
    Chinese Acad Sci, Inst Theoret Phys, Key Lab Theoret Phys, Beijing 100190, Peoples R China.;Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China.;Hunan Normal Univ, Synerget Innovat Ctr Quantum Effects & Applicat, Changsha 410081, Hunan, Peoples R China..
    Aurell, Erik
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Aalto Univ, Dept Appl Phys, Aalto 00076, Finland.;Aalto Univ, Dept Comp Sci, Aalto 00076, Finland..
    Correlation-compressed direct-coupling analysis2018In: Physical review. E, ISSN 2470-0045, E-ISSN 2470-0053, Vol. 98, no 3, article id 032407Article in journal (Refereed)
    Abstract [en]

    Learning Ising or Potts models from data has become an important topic in statistical physics and computational biology, with applications to predictions of structural contacts in proteins and other areas of biological data analysis. The corresponding inference problems are challenging since the normalization constant (partition function) of the Ising or Potts distribution cannot be computed efficiently on large instances. Different ways to address this issue have resulted in a substantial amount of methodological literature. In this paper we investigate how these methods could be used on much larger data sets than studied previously. We focus on a central aspect, that in practice these inference problems are almost always severely under-sampled, and the operational result is almost always a small set of leading predictions. We therefore explore an approach where the data are prefiltered based on empirical correlations, which can be computed directly even for very large problems. Inference is only used on the much smaller instance in a subsequent step of the analysis. We show that in several relevant model classes such a combined approach gives results of almost the same quality as inference on the whole data set. It can therefore provide a potentially very large computational speedup at the price of only marginal decrease in prediction quality. We also show that the results on whole-genome epistatic couplings that were obtained in a recent computation-intensive study can be retrieved by our approach. The method of this paper hence opens up the possibility to learn parameters describing pairwise dependences among whole genomes in a computationally feasible and expedient manner.

  • 4. Ullah, I.
    et al.
    Karthik, G. -M
    Alkodsi, A.
    Kjällquist, U.
    Stålhammar, G.
    Lövrot, J.
    Martinez, N. -F
    Lagergren, Jens
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Hautaniemi, S.
    Hartman, J.
    Bergh, J.
    Evolutionary history of metastatic breast cancer reveals minimal seeding from axillary lymph nodes2018In: Journal of Clinical Investigation, ISSN 0021-9738, E-ISSN 1558-8238, Vol. 128, no 4, p. 1355-1370Article in journal (Refereed)
    Abstract [en]

    Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like-associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.

  • 5. Jordan, Jakob
    et al.
    Ippen, Tammo
    Helias, Moritz
    Kitayama, Itaru
    Sato, Mitsuhisa
    Igarashi, Jun
    Diesmann, Markus
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Julich Res Ctr, Inst Neurosci & Med INM 6, Julich, Germany; Julich Res Ctr, Inst Adv Simulat IAS 6, Julich, Germany; ulich Res Ctr, JARA Inst Brain Struct Funct Relationships INM 10, Julich, Germany; Rhein Westfal TH Aachen, Fac 1, Dept Phys, Aachen, Germany; Julich Res Ctr, Simulat Lab Neurosci, Bernstein Facil Simulat & Da, Julich, Germany.
    Kunkel, Susanne
    Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers2018In: Frontiers in Neuroinformatics, ISSN 1662-5196, E-ISSN 1662-5196, Vol. 12, article id 2Article in journal (Refereed)
    Abstract [en]

    State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

  • 6.
    Aurell, Erik
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Aalto Univ ;Chinese Acad Sci.
    Global Estimates of Errors in Quantum Computation by the Feynman-Vernon Formalism2018In: Journal of statistical physics, ISSN 0022-4715, E-ISSN 1572-9613, Vol. 171, no 5, p. 745-767Article in journal (Refereed)
    Abstract [en]

    The operation of a quantum computer is considered as a general quantum operation on a mixed state on many qubits followed by a measurement. The general quantum operation is further represented as a Feynman-Vernon double path integral over the histories of the qubits and of an environment, and afterward tracing out the environment. The qubit histories are taken to be paths on the two-sphere as in Klauder's coherent-state path integral of spin, and the environment is assumed to consist of harmonic oscillators initially in thermal equilibrium, and linearly coupled to to qubit operators . The environment can then be integrated out to give a Feynman-Vernon influence action coupling the forward and backward histories of the qubits. This representation allows to derive in a simple way estimates that the total error of operation of a quantum computer without error correction scales linearly with the number of qubits and the time of operation. It also allows to discuss Kitaev's toric code interacting with an environment in the same manner.

  • 7. Brasko, Csilla
    et al.
    Smith, Kevin
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Molnar, Csaba
    Farago, Nora
    Hegedus, Lili
    Balind, Arpad
    Balassa, Tamas
    Szkalisity, Abel
    Sukosd, Farkas
    Kocsis, Katalin
    Balint, Balazs
    Paavolainen, Lassi
    Enyedi, Marton Z.
    Nagy, Istvan
    Puskas, Laszlo G.
    Haracska, Lajos
    Tamas, Gabor
    Horvath, Peter
    Intelligent image-based in situ single-cell isolation2018In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, article id 226Article in journal (Refereed)
    Abstract [en]

    Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.

  • 8.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Spatio-temporal scale selection in video data2018In: Journal of Mathematical Imaging and Vision, ISSN 0924-9907, E-ISSN 1573-7683, Vol. 60, no 4, p. 525-562Article in journal (Refereed)
    Abstract [en]

    This work presents a theory and methodology for simultaneous detection of local spatial and temporal scales in video data. The underlying idea is that if we process video data by spatio-temporal receptive fields at multiple spatial and temporal scales, we would like to generate hypotheses about the spatial extent and the temporal duration of the underlying spatio-temporal image structures that gave rise to the feature responses.

    For two types of spatio-temporal scale-space representations, (i) a non-causal Gaussian spatio-temporal scale space for offline analysis of pre-recorded video sequences and (ii) a time-causal and time-recursive spatio-temporal scale space for online analysis of real-time video streams, we express sufficient conditions for spatio-temporal feature detectors in terms of spatio-temporal receptive fields to deliver scale covariant and scale invariant feature responses.

    We present an in-depth theoretical analysis of the scale selection properties of eight types of spatio-temporal interest point detectors in terms of either: (i)-(ii) the spatial Laplacian applied to the first- and second-order temporal derivatives, (iii)-(iv) the determinant of the spatial Hessian applied to the first- and second-order temporal derivatives, (v) the determinant of the spatio-temporal Hessian matrix, (vi) the spatio-temporal Laplacian and (vii)-(viii) the first- and second-order temporal derivatives of the determinant of the spatial Hessian matrix. It is shown that seven of these spatio-temporal feature detectors allow for provable scale covariance and scale invariance. Then, we describe a time-causal and time-recursive algorithm for detecting sparse spatio-temporal interest points from video streams and show that it leads to intuitively reasonable results.

    An experimental quantification of the accuracy of the spatio-temporal scale estimates and the amount of temporal delay obtained these spatio-temporal interest point detectors is given showing that: (i) the spatial and temporal scale selection properties predicted by the continuous theory are well preserved in the discrete implementation and (ii) the spatial Laplacian or the determinant of the spatial Hessian applied to the first- and second-order temporal derivatives lead to much shorter temporal delays in a time-causal implementation compared to the determinant of the spatio-temporal Hessian or the first- and second-order temporal derivatives of the determinant of the spatial Hessian matrix.

  • 9.
    Hussain, Dena
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    The development of ICT tools for E-inclusion qualities: Work in progress2018In: 20th International Conference on Interactive Collaborative Learning, ICL 2017, Springer Verlag , 2018, p. 734-740Conference paper (Refereed)
    Abstract [en]

    With the diversity and increasing use of different information and communication technologies (ICT) in the educational sector, new pedagogic approaches are also being introduced and have had a major impact on the educational sector, focusing on different perspective including improved educational methods and in both schools and homes, information and communication technologies (ICT) are widely seen as enhancing learning, fulfilling their rapid diffusion and acceptance throughout developed societies. But the need to utilize ICT tools to support and guide educators in finding the right support for students with special individual needs is still a challenge, investigating different challenges that are presented to teachers in their working environment is an ongoing matter. One of these challenges that teacher face frequently is creating an inclusive environment. An “inclusive education” is a process of strengthening the capacity of the education system to reach out to all learners involved. It changes the education in content, approaches, structures and strategies, with a common vision that covers all children of the appropriate age range. Inclusion is thus seen as a process of addressing and responding to the diversity of needs of all children. Therefore an inclusive education system can only be created if schools become more inclusive, in other words, if they become better at educating all children in their communities with their individual needs. Therefore, creative forms of communication should be encouraged to promote personalized care, hence the focuses of this research is to investigate the use of data process flow map with the aim to guide the teacher towards an inclusive way of thinking. 

  • 10.
    Jansson, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Krishnasamy, Ezhilmathi
    Leoni, Massimiliano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hoffman, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Time-resolved Adaptive Direct FEM Simulation of High-lift Aircraft Configurations: Chapter in "Numerical Simulation of the Aerodynamics of High-Lift Configurations'", Springer2018In: Numerical Simulation of the Aerodynamics of High-Lift Configurations / [ed] Omar Darío López Mejia andJaime A. Escobar Gomez, Springer, 2018, p. 67-92Chapter in book (Refereed)
    Abstract [en]

    We present an adaptive finite element method for time-resolved simulation of aerodynamics without any turbulence-model parameters, which is applied to a benchmark problem from the HiLiftPW-3workshop to compute the flowpast a JAXA Standard Model (JSM) aircraft model at realistic Reynolds numbers. The mesh is automatically constructed by the method as part of an adaptive algorithm based on a posteriori error estimation using adjoint techniques. No explicit turbulence model is used, and the effect of unresolved turbulent boundary layers is modeled by a simple parametrization of the wall shear stress in terms of a skin friction. In the case of very high Reynolds numbers, we approximate the small skin friction by zero skin friction, corresponding to a free-slip boundary condition, which results in a computational model without any model parameter to be tuned, and without the need for costly boundary-layer resolution. We introduce a numerical tripping-noise term to act as a seed for growth of perturbations; the results support that this triggers the correct physical separation at stall and has no significant pre-stall effect. We show that the methodology quantitavely and qualitatively captures the main features of the JSM experiment-aerodynamic forces and the stall mechanism-with a much coarser mesh resolution and lower computational cost than the state-of-the-art methods in the field, with convergence under mesh refinement by the adaptive method. Thus, the simulation methodology appears to be a possible answer to the challenge of reliably predicting turbulent-separated flows for a complete air vehicle.

  • 11.
    Onishi, Keiji
    et al.
    RIKEN Advanced Institute for Computational Science.
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). RIKEN Advanced Institute for Computational Science.
    Bale, Rahul
    RIKEN Advanced Institute for Computational Science.
    Wang, Wei-Hsiang
    RIKEN Advanced Institute for Computational Science.
    Li, Chung-Gang
    Kobe University and RIKEN Advanced Institute for Computational Science.
    Tsubokura, Makoto
    Kobe University and RIKEN Advanced Institute for Computational Science.
    A Deployment of HPC Algorithm into Pre/Post-Processing for Industrial CFD on K-Computer2017Conference paper (Refereed)
    Abstract [en]

    Pre- and post-processing is still a major problem in industrial computational fluid dynamics (CFD). With the rapid development of computers, physical solvers are getting faster, while pre- remains slow because it's mainly a serial process. A methodology using MPI+OpenMP hybrid parallelization has been proposed to eliminate the manual work required during pre-processing for correcting the surface imperfections of CAD data. Compared to the rapidly increasing amount of data in recent years, the speed-up of visualization is insufficient. We address this limitation of post- by adapting the in-situ visualization to parallelize the post-processing using libsim (Visit) library. The performance of pre-/post- processing is investigated in this work, and we show that the pre-processing time has been reduced from several days in the conventional framework to order of minutes. The post-processing time has been reduced seconds order per frame, and approximately 30% increase of computational time was observed in vehicle aerodynamics cases. 

  • 12. Molnos, Sonja
    et al.
    Mamdouh, Tarek
    Petri, Stefan
    Nocke, Thomas
    Weinkauf, Tino
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Coumou, Dim
    A network-based detection scheme for the jet stream core2017In: Earth System Dynamics, ISSN 2190-4979, E-ISSN 2190-4987, Vol. 8, no 1, p. 75-89Article in journal (Refereed)
    Abstract [en]

    The polar and subtropical jet streams are strong upper-level winds with a crucial influence on weather throughout the Northern Hemisphere midlatitudes. In particular, the polar jet is located between cold arctic air to the north and warmer subtropical air to the south. Strongly meandering states therefore often lead to extreme surface weather. Some algorithms exist which can detect the 2-D (latitude and longitude) jets' core around the hemisphere, but all of them use a minimal threshold to determine the subtropical and polar jet stream. This is particularly problematic for the polar jet stream, whose wind velocities can change rapidly from very weak to very high values and vice versa. We develop a network-based scheme using Dijkstra's shortest-path algorithm to detect the polar and subtropical jet stream core. This algorithm not only considers the commonly used wind strength for core detection but also takes wind direction and climatological latitudinal position into account. Furthermore, it distinguishes between polar and subtropical jet, and between separate and merged jet states. The parameter values of the detection scheme are optimized using simulated annealing and a skill function that accounts for the zonal-mean jet stream position (Rikus, 2015). After the successful optimization process, we apply our scheme to reanalysis data covering 1979-2015 and calculate seasonal-mean probabilistic maps and trends in wind strength and position of jet streams. We present longitudinally defined probability distributions of the positions for both jets for all on the Northern Hemisphere seasons. This shows that winter is characterized by two well-separated jets over Europe and Asia (ca. 20 degrees W to 140 degrees E). In contrast, summer normally has a single merged jet over the western hemisphere but can have both merged and separated jet states in the eastern hemisphere. With this algorithm it is possible to investigate the position of the jets' cores around the hemisphere and it is therefore very suitable to analyze jet stream patterns in observations and models, enabling more advanced model-validation.

  • 13. Karlsson, A.
    et al.
    Olofsson, N.
    Laure, Erwin
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC. KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz). KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Clements, M.
    A parallel microsimulation package for modelling cancer screening policies2017In: Proceedings of the 2016 IEEE 12th International Conference on e-Science, e-Science 2016, IEEE, 2017, p. 323-330Conference paper (Refereed)
    Abstract [en]

    Microsimulation with stochastic life histories is an important tool in the development of public policies. In this article, we use microsimulation to evaluate policies for prostate cancer testing. We implemented the microsimulations as an R package, with pre- and post-processing in R and with the simulations written in C++. Calibrating a microsimulation model with a large population can be computationally expensive. To address this issue, we investigated four forms of parallelism: (i) shared memory parallelism using R; (ii) shared memory parallelism using OpenMP at the C++ level; (iii) distributed memory parallelism using R; and (iv) a hybrid shared/distributed memory parallelism using OpenMP at the C++ level and MPI at the R level. The close coupling between R and C++ offered advantages for ease of software dissemination and the use of high-level R parallelisation methods. However, this combination brought challenges when trying to use shared memory parallelism at the C++ level: the performance gained by hybrid OpenMP/MPI came at the cost of significant re-factoring of the existing code. As a case study, we implemented a prostate cancer model in the microsimulation package. We used this model to investigate whether prostate cancer testing with specific re-testing protocols would reduce harms and maintain any mortality benefit from prostate-specific antigen testing. We showed that four-yearly testing would have a comparable effectiveness and a marked decrease in costs compared with two-yearly testing and current testing. In summary, we developed a microsimulation package in R and assessed the cost-effectiveness of prostate cancer testing. We were able to scale up the microsimulations using a combination of R and C++, however care was required when using shared memory parallelism at the C++ level.

  • 14. Balbi, P.
    et al.
    Massobrio, P.
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms2017In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 13, no 9, article id e1005737Article in journal (Refereed)
    Abstract [en]

    Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.

  • 15.
    Fiebig, Florian
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Edinburgh University, UK.
    Lansner, Anders
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Stockholm University, Sweden.
    A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation2017In: Journal of Neuroscience, ISSN 0270-6474, Vol. 37, no 1, p. 83-96Article in journal (Refereed)
    Abstract [en]

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism.

  • 16.
    Degirmenci, Niyazi Cem
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hoffman, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Arnela, Marc
    Sánchez-Martín, Patricia
    Guasch, Oriol
    Ternström, Sten
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    A Unified Numerical Simulation of Vowel Production That Comprises Phonation and the Emitted Sound2017In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, The International Speech Communication Association (ISCA), 2017, p. 3492-3496Conference paper (Refereed)
    Abstract [en]

    A unified approach for the numerical simulation of vowels is presented, which accounts for the self-oscillations of the vocal folds including contact, the generation of acoustic waves and their propagation through the vocal tract, and the sound emission outwards the mouth. A monolithic incompressible fluid-structure interaction model is used to simulate the interaction between the glottal jet and the vocal folds, whereas the contact model is addressed by means of a level set application of the Eikonal equation. The coupling with acoustics is done through an acoustic analogy stemming from a simplification of the acoustic perturbation equations. This coupling is one-way in the sense that there is no feedback from the acoustics to the flow and mechanical fields. All the involved equations are solved together at each time step and in a single computational run, using the finite element method (FEM). As an application, the production of vowel [i] has been addressed. Despite the complexity of all physical phenomena to be simulated simultaneously, which requires resorting to massively parallel computing, the formant locations of vowel [i] have been well recovered.

  • 17.
    Avramova, Vanya
    et al.
    KTH.
    Yang, Fangkai
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Li, Chengjie
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Peters, Christopher
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Skantze, Gabriel
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    A virtual poster presenter using mixed reality2017In: 17th International Conference on Intelligent Virtual Agents, IVA 2017, Springer, 2017, Vol. 10498, p. 25-28Conference paper (Refereed)
    Abstract [en]

    In this demo, we will showcase a platform we are currently developing for experimenting with situated interaction using mixed reality. The user will wear a Microsoft HoloLens and be able to interact with a virtual character presenting a poster. We argue that a poster presentation scenario is a good test bed for studying phenomena such as multi-party interaction, speaker role, engagement and disengagement, information delivery, and user attention monitoring.

  • 18. Spreizer, Sebastian
    et al.
    Angelhuber, Martin
    Bahuguna, Jyotika
    Aertsen, Ad
    Kumar, Arvind
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity2017In: eNeuro, ISSN 2373-2822Article in journal (Refereed)
    Abstract [en]

    The striatum is the main input nucleus of the basal ganglia. Characterizing striatal activity dynamics is crucial to understanding mechanisms underlying action-selection, -initiation and -execution. Here, we studied the effects of spatial network connectivity on the spatio-temporal structure of striatal activity. We show that a striatal network with non-monotonically changing distance-dependent connectivity (according to a Gamma distribution) can exhibit a wide repertoire of spatio-temporal dynamics, ranging from spatially homogeneous asynchronous-irregular (AI) activity to a state with stable, spatially localized activity bumps, as in ‘winner-take-all’ (WTA) dynamics. Among these regimes, the unstable activity bumps (Transition Activity, TA) regime closely resembles the experimentally observed spatio-temporal activity dynamics and neuronal assemblies in the striatum. By contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can only exhibit an AI state. Thus, given the observation of spatially compact neuronal clusters in the striatum, our model suggests that recurrent connectivity among striatal projection neurons should vary non-monotonically. In brain disorders such as Parkinson’s disease, increased cortical inputs and high striatal firing rates are associated with a reduction in stimulus sensitivity. Consistent with this, our model suggests that strong cortical inputs drive the striatum to a WTA state, leading to low stimulus sensitivity and high variability. By contrast, the AI and TA states show high stimulus sensitivity and reliability. Thus, based on these results, we propose that in a healthy state the striatum operates in a AI/TA state and that lack of dopamine pushes it into a WTA state.Significance Statement Recent findings suggest that striatal activity is organized in spatially compact neuron clusters. Here, we show that striatal projection neurons should have a non-monotonically changing distance-dependent connectivity to obtain spatially localized activity patterns in striatum. Among the different states a striatal network can show, asynchronous-irregular and transition activity states closely resemble striatal activity in the healthy state. By contrast, strong cortical inputs as observed in Parkinson’s disease (PD) drive the network into a winner-take-all state, in which the striatum looses its stimulus sensitivity. Thus, our model makes specific predictions about the spatial network connectivity in the striatum and provides new insights about how the striatum might make a transition from a healthy state to a PD state.

  • 19.
    Jansson, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Degirmenci, N. C.
    KTH, School of Computer Science and Communication (CSC).
    Hoffman, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Adaptive unified continuum FEM modeling of a 3D FSI benchmark problem2017In: International Journal for Numerical Methods in Biomedical Engineering, ISSN 2040-7939, E-ISSN 2040-7947, Vol. 33, no 9, article id e2851Article in journal (Refereed)
    Abstract [en]

    In this paper, we address a 3D fluid-structure interaction benchmark problem that represents important characteristics of biomedical modeling. We present a goal-oriented adaptive finite element methodology for incompressible fluid-structure interaction based on a streamline diffusion–type stabilization of the balance equations for mass and momentum for the entire continuum in the domain, which is implemented in the Unicorn/FEniCS software framework. A phase marker function and its corresponding transport equation are introduced to select the constitutive law, where the mesh tracks the discontinuous fluid-structure interface. This results in a unified simulation method for fluids and structures. We present detailed results for the benchmark problem compared with experiments, together with a mesh convergence study.

  • 20. Piccinini, Filippo
    et al.
    Balassa, Tamas
    Szkalisity, Abel
    Molnar, Csaba
    Paavolainen, Lassi
    Kujala, Kaisa
    Buzas, Krisztina
    Sarazova, Marie
    Pietiainen, Vilja
    Kutay, Ulrike
    Smith, Kevin
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Horvath, Peter
    Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data2017In: CELL SYSTEMS, ISSN 2405-4712, Vol. 4, no 6, p. 651-+Article in journal (Refereed)
    Abstract [en]

    High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org.

  • 21. Iatropoulos, Georgios
    et al.
    Olofsson, Jonas
    Herman, Pawel
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lansner, Anders
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Larsson, Maria
    Analysis of Statistics and Semantic Relations of Odor-Describing Words in Written Olfactory Versus Non- Olfactory Contexts2017In: Chemical Senses, ISSN 0379-864X, E-ISSN 1464-3553, Vol. 42, no 2, p. E34-E35Article in journal (Refereed)
  • 22. Mbuvha, R.
    et al.
    Jonsson, M.
    Ehn, N.
    Herman, Pawel
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Bayesian neural networks for one-hour ahead wind power forecasting2017In: 2017 6th International Conference on Renewable Energy Research and Applications, ICRERA 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, Vol. 2017, p. 591-596Conference paper (Refereed)
    Abstract [en]

    The greatest concern facing renewable energy sources like wind is the uncertainty in production volumes as their generation ability is inherently dependent on weather conditions. When providing forecasts for newly commissioned wind farms there is a limited amount of historical power production data, while the number of potential features from different weather forecast providers is vast. Bayesian regularization is therefore seen as a possible technique for reducing model overfitting problems that may arise. This work investigates Bayesian Neural Networks for one-hour ahead forecasting of wind power generation. Initial results show that Bayesian Neural Networks display equivalent predictive performance to Neural Networks trained by Maximum Likelihood. Further results show that Bayesian Neural Networks become superior after removing irrelevant features using Automatic Relevance Determination(ARD).

  • 23.
    Saikia, Himangshu
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Comparison and Tracking Methods for Interactive Visualization of Topological Structures in Scalar Fields2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Scalar fields occur quite commonly in several application areas in both static and time-dependent forms. Hence a proper visualization of scalar fieldsneeds to be equipped with tools to extract and focus on important features of the data. Similarity detection and pattern search techniques in scalar fields present a useful way of visualizing important features in the data. This is done by isolating these features and visualizing them independently or show all similar patterns that arise from a given search pattern. Topological features are ideal for this purpose of isolating meaningful patterns in the data set and creating intuitive feature descriptors. The Merge Tree is one such topological feature which has characteristics ideally suited for this purpose. Subtrees of merge trees segment the data into hierarchical regions which are topologically defined. This kind of feature-based segmentation is more intelligent than pure data based segmentations involving windows or bounding volumes. In this thesis, we explore several different techniques using subtrees of merge trees as features in scalar field data. Firstly, we begin with a discussion on static scalar fields and devise techniques to compare features - topologically segmented regions given by the subtrees of the merge tree - against each other. Second, we delve into time-dependent scalar fields and extend the idea of feature comparison to spatio-temporal features. In this process, we also come up with a novel approach to track features in time-dependent data considering the entire global network of likely feature associations between consecutive time steps.The highlight of this thesis is the interactivity that is enabled using these feature-based techniques by the real-time computation speed of our algorithms. Our techniques are implemented in an open-source visualization framework Inviwo and are published in several peer-reviewed conferences and journals.

  • 24.
    Iakymchuk, Roman
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Shakhno, S. M.
    Yarmola, H. P.
    CONVERGENCE ANALYSIS OF A TWO-STEP MODIFICATION OF THE GAUSS-NEWTON METHOD AND ITS APPLICATIONS2017In: JOURNAL OF NUMERICAL AND APPLIED MATHEMATICS, ISSN 0868-6912, Vol. 3, no 126, p. 61-74Article in journal (Refereed)
    Abstract [en]

    We investigate the convergence of a two-step modification of the Gauss-Newton method applying the generalized Lipschitz condition for the first- and second-order derivatives. The convergence order as well as the convergence radius of the method are studied and the uniqueness ball of the solution of the nonlinear least squares problem is examined. Finally, we carry out numerical experiments on a set of well-known test problems.

  • 25. Szalisznyó, K.
    et al.
    Silverstein, David
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Karolinska Institutet, Sweden.
    Teichmann, M.
    Duffau, H.
    Smits, A.
    Cortico-striatal language pathways dynamically adjust for syntactic complexity: A computational study2017In: Brain and Language, ISSN 0093-934X, E-ISSN 1090-2155, Vol. 164, p. 53-62Article in journal (Refereed)
    Abstract [en]

    A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity.

  • 26.
    Peng, Ivy Bo
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Data Movement on Emerging Large-Scale Parallel Systems2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Large-scale HPC systems are an important driver for solving computational problems in scientific communities. Next-generation HPC systems will not only grow in scale but also in heterogeneity. This increased system complexity entails more challenges to data movement in HPC applications. Data movement on emerging HPC systems requires asynchronous fine-grained communication and efficient data placement in the main memory. This thesis proposes an innovative programming model and algorithm to prepare HPC applications for the next computing era: (1) a data streaming model that supports emerging data-intensive applications on supercomputers, (2) a decoupling model that improves parallelism and mitigates the impact of imbalance in applications, (3) a new framework and methodology for predicting the impact of largescale heterogeneous memory systems on HPC applications, and (4) a data placement algorithm that uses a set of rules and a decision tree to determine the data-to-memory mapping in heterogeneous main memory.

    The proposed approaches in this thesis are evaluated on multiple supercomputers with different processors and interconnect networks. The evaluation uses a diverse set of applications that represent conventional scientific applications and emerging data-analytic workloads on HPC systems. The experimental results on the petascale testbed show that the approaches obtain increasing performance improvements as system scale increases and this trend supports the approaches as a valuable contribution towards future HPC systems.

  • 27.
    Herman, Pawel
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Prasad, Girijesh
    McGinnity, Thomas Martin
    Designing an Interval Type-2 Fuzzy Logic System for Handling Uncertainty Effects in Brain-Computer Interface Classification of Motor Imagery Induced EEG Patterns2017In: IEEE transactions on fuzzy systems, ISSN 1063-6706, E-ISSN 1941-0034, Vol. 25, no 1, p. 29-42Article in journal (Refereed)
    Abstract [en]

    One of the urgent challenges in the automated analysis and interpretation of electrical brain activity is the effective handling of uncertainties associated with the complexity and variability of brain dynamics, reflected in the nonstationary nature of brain signals such as electroencephalogram (EEG). This poses a severe problem for existing approaches to the classification task within brain-computer interface (BCI) systems. Recently emerged type-2 fuzzy logic (T2FL) methodology has shown a remarkable potential in dealing with uncertain information given limited insight into the nature of the data-generating mechanism. The objective of this work is, thus, to examine the applicability of the T2FL approach to the problem of EEG pattern recognition. In particular, the focus is two-fold: 1) the design methodology for the interval T2FL system (IT2FLS) that can robustly deal with inter-session as well as within-session manifestations of nonstationary spectral EEG correlates of motor imagery, and 2) the comprehensive examination of the proposed fuzzy classifier in both off-line and on-line EEG classification case studies. The on-line evaluation of the IT2FLS-controlled real-time neurofeedback over multiple recording sessions holds special importance for EEG-based BCI technology. In addition, a retrospective comparative analysis accounting for other popular BCI classifiers such as linear discriminant analysis, kernel Fisher discriminant, and support vector machines as well as a conventional type-1 FLS, simulated off-line on the recorded EEGs, has demonstrated the enhanced potential of the proposed IT2FLS approach to robustly handle uncertainty effects in BCI classification.

  • 28.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Discrete approximations of affine Gaussian receptive fields2017Report (Other academic)
    Abstract [en]

    This paper presents a theory for discretizing the affine Gaussian scale-space concept so that scale-space properties hold also for the discrete implementation.

    Two ways of discretizing spatial smoothing with affine Gaussian kernels are presented: (i) by solving semi-discretized affine diffusion equation as derived by necessity from the requirement of a semi-group structure over a continuum of scale parameters as parameterized by a family of spatial covariance matrices and obeying non-creation of new structures from any finer to any coarser scale as formalized by the requirement of non-enhancement of local extrema and (ii) a set of parameterized 3x3-kernels as derived from an additional discretization of the above theory along the scale direction and with the parameters of the kernels having a direct interpretation in terms of the covariance matrix of the composed discrete smoothing operation.

    We show how convolutions with the first family of kernels can be implemented in terms of a closed form expression for the Fourier transform and analyse how a remaining degree of freedom in the theory can be explored to ensure a positive discretization and optionally also achieve higher-order discrete approximation of the angular dependency of the shapes of the affine Gaussian kernels.

    We do also show how discrete directional derivative approximations can be efficiently implemented to approximate affine Gaussian derivatives as constituting a canonical model for receptive fields over a purely spatial image domain and with close relations to receptive fields in biological vision.

  • 29.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Discrete approximations of the affine Gaussian derivative model for visual receptive fields2017Report (Other academic)
    Abstract [en]

    The affine Gaussian derivative model can in several respects be regarded as a canonical model for receptive fields over a spatial image domain: (i) it can be derived by necessity from scale-space axioms that reflect structural properties of the world, (ii) it constitutes an excellent model for the receptive fields of simple cells in the primary visual cortex and (iii) it is covariant under affine image deformations, which enables more accurate modelling of image measurements under the local image deformations caused by the perspective mapping, compared to the more commonly used Gaussian derivative model based on derivatives of the rotationally symmetric Gaussian kernel.

    This paper presents a theory for discretizing the affine Gaussian scale-space concept underlying the affine Gaussian derivative model, so that scale-space properties hold also for the discrete implementation.

    Two ways of discretizing spatial smoothing with affine Gaussian kernels are presented: (i) by solving a semi-discretized affine diffusion equation, which has derived by necessity from the requirements of a semi-group structure over scale as parameterized by a family of spatial covariance matrices and obeying non-creation of new structures from any finer to any coarser scale in terms of non-enhancement of local extrema and (ii) approximating these semi-discrete affine receptive fields by parameterized families of 3x3-kernels as obtained from an additional discretization along the scale direction. The latter discrete approach can be optionally complemented by spatial subsampling at coarser scales, leading to the notion of affine hybrid pyramids.

    For the first approach, we show how the solutions can be computed from a closed form expression for the Fourier transform, and analyse how a remaining degree of freedom in the theory can be explored to ensure a positive discretization and optionally achieve higher-order discrete approximation of the angular dependency of the discrete affine Gaussian receptive fields. For the second approach, we analyse how the step length in the scale direction can be determined, given the requirements of a positive discretization.

    We do also show how discrete directional derivative approximations can be efficiently implemented to approximate affine Gaussian derivatives. Using these theoretical results, we outline hybrid architectures for discrete approximations of affine covariant receptive field families, to be used as a first processing layer for affine covariant and affine invariant visual operations at higher levels.

  • 30.
    Jansson, Ylva
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields2017Report (Other academic)
    Abstract [en]

    This work presents a first evaluation of using spatiotemporal receptive fields from a recently proposed time-causal spatio-temporal scale-space framework as primitives for video analysis. We propose a new family of video descriptors based on regional statistics of spatio-temporal receptive field responses and evaluate this approach on the problem of dynamic texture recognition. Our approach generalises a previously used method, based on joint histograms of receptive field responses, from the spatial to the spatio-temporal domain and from object recognition to dynamic texture recognition. The time-recursive formulation enables computationally efficient time-causal recognition.

    The experimental evaluation demonstrates competitive performance compared to state-of-the-art. Especially, it is shown that binary versions of our dynamic texture descriptors achieve improved performance compared to a large range of similar methods using different primitives either handcrafted or learned from data. Further, our qualitative and quantitative investigation into parameter choices and the use of different sets of receptive fields highlights the robustness and flexibility of our approach. Together, these results support the descriptive power of this family of time-causal spatio-temporal receptive fields, validate our approach for dynamic texture recognition and point towards the possibility of designing a range of video analysis methods based on these new time-causal spatio-temporal primitives.

  • 31.
    Jansson, Ylva
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Dynamic texture recognition using time-causal spatio-temporal scale-space filters2017In: Scale Space and Variational Methods in Computer Vision, Springer, 2017, Vol. 10302, p. 16-28Conference paper (Refereed)
    Abstract [en]

    This work presents an evaluation of using time-causal scale-space filters as primitives for video analysis. For this purpose, we present a new family of video descriptors based on regional statistics of spatiotemporal scale-space filter responses and evaluate this approach on the problem of dynamic texture recognition. Our approach generalises a previously used method, based on joint histograms of receptive field responses, from the spatial to the spatio-temporal domain. We evaluate one member in this family, constituting a joint binary histogram, on two widely used dynamic texture databases. The experimental evaluation shows competitive performance compared to previous methods for dynamic texture recognition, especially on the more complex DynTex database. These results support the descriptive power of time-causal spatio-temporal scale-space filters as primitives for video analysis.

  • 32. Deca, Jan
    et al.
    Divin, Andrey
    Henri, Pierre
    Eriksson, Anders
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Olshevsky, Vyacheslav
    Horanyi, Mihaly
    Electron and Ion Dynamics of the Solar Wind Interaction with a Weakly Outgassing Comet2017In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 118, no 20, article id 205101Article in journal (Refereed)
    Abstract [en]

    Using a 3D fully kinetic approach, we disentangle and explain the ion and electron dynamics of the solar wind interaction with a weakly outgassing comet. We show that, to first order, the dynamical interaction is representative of a four-fluid coupled system. We self-consistently simulate and identify the origin of the warm and suprathermal electron distributions observed by ESA's Rosetta mission to comet 67P/Churyumov-Gerasimenko and conclude that a detailed kinetic treatment of the electron dynamics is critical to fully capture the complex physics of mass-loading plasmas.

  • 33. Khotyaintsev, Yu. V.
    et al.
    Divin, A.
    Vaivads, A.
    Andre, M.
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Energy conversion at dipolarization fronts2017In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 44, no 3, p. 1234-1242Article in journal (Refereed)
    Abstract [en]

    We use multispacecraft observations by Cluster in the Earth's magnetotail and 3-D particle-in-cell simulations to investigate conversion of electromagnetic energy at the front of a fast plasma jet. We find that the major energy conversion is happening in the Earth (laboratory) frame, where the electromagnetic energy is being transferred from the electromagnetic field to particles. This process operates in a region with size of the order several ion inertial lengths across the jet front, and the primary contribution to E . j is coming from the motional electric field and the ion current. In the frame of the front we find fluctuating energy conversion with localized loads and generators at sub-ion scales which are primarily related to the lower hybrid drift instability excited at the front; however, these provide relatively small net energy conversion.

  • 34. Lapenta, Giovanni
    et al.
    Goldman, Martin V.
    Newman, David L.
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Energy exchanges in reconnection outflows2017In: Plasma Physics and Controlled Fusion, ISSN 0741-3335, E-ISSN 1361-6587, Vol. 59, no 1, article id 014019Article in journal (Refereed)
    Abstract [en]

    Reconnection outflows are highly energetic directed flows that interact with the ambient plasma or with flows from other reconnection regions. Under these conditions the flow becomes highly unstable and chaotic, as any flow jets interacting with a medium. We report here massively parallel simulations of the two cases of interaction between outflow jets and between a single outflow with an ambient plasma. We find in both case the development of a chaotic magnetic field, subject to secondary reconnection events that further complicate the topology of the field lines. The focus of the present analysis is on the energy balance. We compute each energy channel (electromagnetic, bulk, thermal, for each species) and find where the most energy is exchanged and in what form. The main finding is that the largest energy exchange is not at the reconnection site proper but in the regions where the outflowing jets are destabilized.

  • 35.
    Larsson, David
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Imaging. Karolinska Insitutet, Sweden.
    Spühler, Jeannette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Günyeli, E.
    Weinkauf, Tino
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hoffman, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Colarieti-Tosti, Massimiliano
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Imaging. Karolinska Institutet, Sweden.
    Winter, R.
    Larsson, Matilda
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Imaging. Karolinska Institutet, Sweden.
    Estimation of left ventricular blood flow parameters: Clinical application of patient-specific CFD simulations from 4D echocardiography2017In: Medical Imaging 2017: Ultrasonic Imaging and Tomography, SPIE - International Society for Optical Engineering, 2017, Vol. 10139, article id 101390LConference paper (Refereed)
    Abstract [en]

    Echocardiography is the most commonly used image modality in cardiology, assessing several aspects of cardiac viability. The importance of cardiac hemodynamics and 4D blood flow motion has recently been highlighted, however such assessment is still difficult using routine echo-imaging. Instead, combining imaging with computational fluid dynamics (CFD)-simulations has proven valuable, but only a few models have been applied clinically. In the following, patient-specific CFD-simulations from transthoracic dobutamin stress echocardiography have been used to analyze the left ventricular 4D blood flow in three subjects: two with normal and one with reduced left ventricular function. At each stress level, 4D-images were acquired using a GE Vivid E9 (4VD, 1.7MHz/3.3MHz) and velocity fields simulated using a presented pathway involving endocardial segmentation, valve position identification, and solution of the incompressible Navier-Stokes equation. Flow components defined as direct flow, delayed ejection flow, retained inflow, and residual volume were calculated by particle tracing using 4th-order Runge-Kutta integration. Additionally, systolic and diastolic average velocity fields were generated. Results indicated no major changes in average velocity fields for any of the subjects. For the two subjects with normal left ventricular function, increased direct flow, decreased delayed ejection flow, constant retained inflow, and a considerable drop in residual volume was seen at increasing stress. Contrary, for the subject with reduced left ventricular function, the delayed ejection flow increased whilst the retained inflow decreased at increasing stress levels. This feasibility study represents one of the first clinical applications of an echo-based patient-specific CFD-model at elevated stress levels, and highlights the potential of using echo-based models to capture highly transient flow events, as well as the ability of using simulation tools to study clinically complex phenomena. With larger patient studies planned for the future, and with the possibility of adding more anatomical features into the model framework, the current work demonstrates the potential of patient-specific CFD-models as a tool for quantifying 4D blood flow in the heart.

  • 36.
    Peng, I. Bo
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Laure, Erwin
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Kestor, G.
    Gioiosa, R.
    Exploring Application Performance on Emerging Hybrid-Memory Supercomputers2017In: Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 473-480, article id 7828415Conference paper (Refereed)
    Abstract [en]

    Next-generation supercomputers will feature more hierarchical and heterogeneous memory systems with different memory technologies working side-by-side. A critical question is whether at large scale existing HPC applications and emerging data-analytics workloads will have performance improvement or degradation on these systems. We propose a systematic and fair methodology to identify the trend of application performance on emerging hybrid-memory systems. We model the memory system of next-generation supercomputers as a combination of 'fast' and 'slow' memories. We then analyze performance and dynamic execution characteristics of a variety of workloads, from traditional scientific applications to emerging data analytics to compare traditional and hybrid-memory systems. Our results show that data analytics applications can clearly benefit from the new system design, especially at large scale. Moreover, hybrid-memory systems do not penalize traditional scientific applications, which may also show performance improvement.

  • 37. Paetzel, M.
    et al.
    Hupont, I.
    Varni, G.
    Chetouani, M.
    Peters, Christopher
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz). KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Castellano, G.
    Exploring the link between self-assessed mimicry and embodiment in HRI2017In: ACM/IEEE International Conference on Human-Robot Interaction, IEEE Computer Society , 2017, p. 245-246Conference paper (Refereed)
    Abstract [en]

    This work explores the relationship between a robot's embodiment and people's ability to mimic its behavior. It presents a study in which participants were asked to mimic a 3D mixed-embodied robotic head and a 2D version of the same character. Quantitative and qualitative analysis were performed from questionnaires. Quantitative results show no significant influence of the character's embodiment on the self-assessed ability to mimic it, while qualitative ones indicate a preference for mimicking the robotic head.

  • 38.
    Peng, I. B.
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Gioiosa, R.
    Kestor, G.
    Cicotti, P.
    Laure, Erwin
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Exploring the performance benefit of hybrid memory system on HPC environments2017In: Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 683-692, article id 7965110Conference paper (Refereed)
    Abstract [en]

    Hardware accelerators have become a de-facto standard to achieve high performance on current supercomputers and there are indications that this trend will increase in the future. Modern accelerators feature high-bandwidth memory next to the computing cores. For example, the Intel Knights Landing (KNL) processor is equipped with 16 GB of high-bandwidth memory (HBM) that works together with conventional DRAM memory. Theoretically, HBM can provide ∼4× higher bandwidth than conventional DRAM. However, many factors impact the effective performance achieved by applications, including the application memory access pattern, the problem size, the threading level and the actual memory configuration. In this paper, we analyze the Intel KNL system and quantify the impact of the most important factors on the application performance by using a set of applications that are representative of scientific and data-analytics workloads. Our results show that applications with regular memory access benefit from MCDRAM, achieving up to 3× performance when compared to the performance obtained using only DRAM. On the contrary, applications with random memory access pattern are latency-bound and may suffer from performance degradation when using only MCDRAM. For those applications, the use of additional hardware threads may help hide latency and achieve higher aggregated bandwidth when using HBM.

  • 39.
    Yang, Fangkai
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Li, Chengjie
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Palmberg, Robin
    KTH, School of Computer Science and Communication (CSC).
    Van der Heide, Ewoud
    KTH, School of Computer Science and Communication (CSC).
    Peters, Christopher
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Expressive Virtual Characters for Social Demonstration Games2017In: 2017 9th International Conference on Virtual Worlds and Games for Serious Applications, VS-Games 2017 - Proceedings, IEEE, 2017, p. 217-224Conference paper (Refereed)
    Abstract [en]

    Virtual characters are an integral part of many game and learning environments and have practical applications as tutors, demonstrators or even representations of the user. However, creating virtual character behaviors can be a time-consuming and complex task requiring substantial technical expertise. To accelerate and better enable the use of virtual characters in social games, we present a virtual character behavior toolkit for the development of expressive virtual characters. It is a midlleware toolkit which sits on top of the game engine with a focus on providing high-level character behaviors to quickly create social games. The toolkit can be adapted to a wide range of scenarios related to social interactions with individuals and groups at multiple distances in the virtual environment and supports customization and control of facial expressions, body animations and group formations. We describe the design of the toolkit, providing an examplar of a small game that is being created with it and our intended future work on the system.

  • 40.
    Rivas-Gomez, Sergio
    et al.
    KTH, School of Computer Science and Communication (CSC).
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Peng, Ivy Bo
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Laure, E.
    Kestor, G.
    Gioiosa, R.
    Extending message passing interface windows to storage2017In: Proceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017, Institute of Electrical and Electronics Engineers Inc. , 2017, p. 728-730Conference paper (Refereed)
    Abstract [en]

    This paper presents an extension to MPI supporting the one-sided communication model and window allocations in storage. Our design transparently integrates with the current MPI implementations, enabling applications to target MPI windows in storage, memory or both simultaneously, without major modifications. Initial performance results demonstrate that the presented MPI window extension could potentially be helpful for a wide-range of use-cases and with low-overhead.

  • 41. Frånberg, Mattias
    et al.
    Strawbridge, Rona J.
    Hamsten, Anders
    de Faire, Ulf
    Lagergren, Jens
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Sennblad, Bengt
    Fast and general tests of genetic interaction for genome-wide association studies2017In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 13, no 6, article id e1005556Article in journal (Refereed)
    Abstract [en]

    A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two 'tag' variants in the LPA locus (p = 2.42 . 10(-09)) as well as replicate the interaction (p = 6.97 . 10(-07)). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.

  • 42.
    Hoffman, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC). Basque Center for Applied Mathematics (BCAM), Bilbao, Spain.
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Basque Center for Applied Mathematics (BCAM), Bilbao, Spain.
    Degirmenci, Niyazi Cem
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Spühler, Jeannette Hiromi
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Vilela de Abreu, Rodrigo
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Jansson, Niclas
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Larcher, Aurélien
    Norwegian University of Science and Technology, Trondheim, Norway.
    FEniCS-HPC: Coupled Multiphysics in Computational Fluid Dynamics2017In: High-Performance Scientific Computing: Jülich Aachen Research Alliance (JARA) High-Performance Computing Symposium / [ed] Edoardo Di Napoli, Marc-André Hermanns, Hristo Iliev, Andreas Lintermann, Alexander Peyser, Springer, 2017, p. 58-69Conference paper (Refereed)
    Abstract [en]

    We present a framework for coupled multiphysics in computational fluid dynamics, targeting massively parallel systems. Our strategy is based on general problem formulations in the form of partial differential equations and the finite element method, which open for automation, and optimization of a set of fundamental algorithms. We describe these algorithms, including finite element matrix assembly, adaptive mesh refinement and mesh smoothing; and multiphysics coupling methodologies such as unified continuum fluid-structure interaction (FSI), and aeroacoustics by coupled acoustic analogies. The framework is implemented as FEniCS open source software components, optimized for massively parallel computing. Examples of applications are presented, including simulation of aeroacoustic noise generated by an airplane landing gear, simulation of the blood flow in the human heart, and simulation of the human voice organ.

  • 43.
    Saikia, Himangshu
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Weinkauf, Tino
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Global Feature Tracking and Similarity Estimation in Time-Dependent Scalar Fields2017In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 36, no 3, p. 1-11Article in journal (Refereed)
    Abstract [en]

    We present an algorithm for tracking regions in time-dependent scalar fields that uses global knowledge from all time steps for determining the tracks. The regions are defined using merge trees, thereby representing a hierarchical segmentation of the data in each time step. The similarity of regions of two consecutive time steps is measured using their volumetric overlap and a histogram difference. The main ingredient of our method is a directed acyclic graph that records all relevant similarity information as follows: the regions of all time steps are the nodes of the graph, the edges represent possible short feature tracks between consecutive time steps, and the edge weights are given by the similarity of the connected regions. We compute a feature track as the global solution of a shortest path problem in the graph. We use these results to steer the - to the best of our knowledge - first algorithm for spatio-temporal feature similarity estimation. Our algorithm works for 2D and 3D time-dependent scalar fields. We compare our results to previous work, showcase its robustness to noise, and exemplify its utility using several real-world data sets.

  • 44. Bahuguna, Jyotika
    et al.
    Tetzlaff, Tom
    Kumar, Arvind
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Morrison, Abigail
    Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions2017In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 11, article id 79Article in journal (Refereed)
    Abstract [en]

    The classical model of basal ganglia has been refined in recent years with discoveries of subpopulations within a nucleus and previously unknown projections. One such discovery is the presence of subpopulations of arkypallidal and prototypical neurons in external globus pallidus, which was previously considered to be a primarily homogeneous nucleus. Developing a computational model of these multiple interconnected nuclei is challenging, because the strengths of the connections are largely unknown. We therefore use a genetic algorithm to search for the unknown connectivity parameters in a firing rate model. We apply a binary cost function derived from empirical firing rate and phase relationship data for the physiological and Parkinsonian conditions. Our approach generates ensembles of over 1,000 configurations, or homologies, for each condition, with broad distributions for many of the parameter values and overlap between the two conditions. However, the resulting effective weights of connections from or to prototypical and arkypallidal neurons are consistent with the experimental data. We investigate the significance of the weight variability by manipulating the parameters individually and cumulatively, and conclude that the correlation observed between the parameters is necessary for generating the dynamics of the two conditions. We then investigate the response of the networks to a transient cortical stimulus, and demonstrate that networks classified as physiological effectively suppress activity in the internal globus pallidus, and are not susceptible to oscillations, whereas parkinsonian networks show the opposite tendency. Thus, we conclude that the rates and phase relationships observed in the globus pallidus are predictive of experimentally observed higher level dynamical features of the physiological and parkinsonian basal ganglia, and that the multiplicity of solutions generated by our method may well be indicative of a natural diversity in basal ganglia networks. We propose that our approach of generating and analyzing an ensemble of multiple solutions to an underdetermined network model provides greater confidence in its predictions than those derived from a unique solution, and that projecting such homologous networks on a lower dimensional space of sensibly chosen dynamical features gives a better chance than a purely structural analysis at understanding complex pathologies such as Parkinson's disease.

  • 45.
    de Giorgio, Andrea
    et al.
    KTH.
    Romero, Mario
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Onori, Mauro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Human-machine Collaboration in Virtual Reality for Adaptive Production Engineering2017In: Procedia Manufacturing, ISSN 2351-9789, Vol. 11, p. 1279-1287Article in journal (Refereed)
    Abstract [en]

    This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.

  • 46.
    Peng, I. Bo
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Laure, Erwin
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Kestor, G.
    Gioiosa, R.
    Idle period propagation in message-passing applications2017In: Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 937-944, article id 7828475Conference paper (Refereed)
    Abstract [en]

    Idle periods on different processes of Message Passing applications are unavoidable. While the origin of idle periods on a single process is well understood as the effect of system and architectural random delays, yet it is unclear how these idle periods propagate from one process to another. It is important to understand idle period propagation in Message Passing applications as it allows application developers to design communication patterns avoiding idle period propagation and the consequent performance degradation in their applications. To understand idle period propagation, we introduce a methodology to trace idle periods when a process is waiting for data from a remote delayed process in MPI applications. We apply this technique in an MPI application that solves the heat equation to study idle period propagation on three different systems. We confirm that idle periods move between processes in the form of waves and that there are different stages in idle period propagation. Our methodology enables us to identify a self-synchronization phenomenon that occurs on two systems where some processes run slower than the other processes.

  • 47. Skwark, Marcin J.
    et al.
    Croucher, Nicholas J.
    Puranen, Santeri
    Chewapreecha, Claire
    Pesonen, Maiju
    Xu, Ying Ying
    Turner, Paul
    Harris, Simon R.
    Beres, Stephen B.
    Musser, James M.
    Parkhill, Julian
    Bentley, Stephen D.
    Aurell, Erik
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Corander, Jukka
    Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis2017In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 2, article id e1006508Article in journal (Refereed)
    Abstract [en]

    Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein- protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.

  • 48.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Bernstein Center Freiburg, University of Freiburg, Freiburg Germany.
    Kumar, Arvind
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Bernstein Center Freiburg, University of Freiburg, Freiburg Germany.
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
    Interactions in the Striatal Network with Different Oscillation Frequencies2017In: Artificial Neural Networks and Machine Learning – ICANN. Lecture Notes in Computer Science, Springer, 2017, Vol. 10613, p. 129-136Conference paper (Refereed)
    Abstract [en]

    Simultaneous oscillations in different frequency bands are implicated in the striatum, and understanding their interactions will bring us one step closer to restoring the spectral characteristics of striatal activity that correspond to the healthy state. We constructed a computational model of the striatum in order to investigate how different, simultaneously present, and externally induced oscillations propagate through striatal circuitry and which stimulation parameters have a significant contribution. Our results show that features of these oscillations and their interactions can be influenced via amplitude, input frequencies, and the phase offset between different external inputs. Our findings provide further untangling of the oscillatory activity that can be seen within the striatal network.

  • 49. Wendt, Fabian F
    et al.
    Yu, Yi-Hsiang
    Nielsen, Kim
    Ruehl, Kelley
    Bunnik, Tim
    Touzon, Imanol
    Nam, Bo Woo
    Kim, Jeong Seok
    Kim, Kyong-Hwan
    Janson, Carl Erik
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hoffman, Johan
    et al.,
    International Energy Agency Ocean Energy Systems Task 10 Wave Energy Converter Modeling Verification and Validation2017In: 12th European Wave and Tidal Energy Conference European Wave and Tidal Energy Conference, 2017Conference paper (Refereed)
  • 50.
    Belić, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Kumar, Arvind
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 4, p. 1-17Article in journal (Refereed)
    Abstract [en]

    Network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease. The striatum, the main input nucleus of the basal ganglia, receives massive glutamatergic inputs from the cortex and is highly susceptible to external oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. Using a network model of the striatum and corticostriatal projections, we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Here, we propose that fast-spiking interneurons can perform an important role in transferring cortical oscillations to the striatum especially to those medium spiny neurons that are not directly driven by the cortical oscillations. We show how the activity levels of different populations, the strengths of different inhibitory synapses, degree of outgoing projections of striatal cells, ongoing activity and synchronicity of inputs can influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is most efficient, if conveyed via the fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.

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