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  • 1.
    Aguilar, Xavier
    et al.
    KTH, Centres, SeRC - Swedish e-Science Research Centre.
    Fürlinger, K.
    Laure, Erwin
    KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Online MPI trace compression using event flow graphs and wavelets2016In: Procedia Computer Science, Elsevier, 2016, p. 1497-1506Conference paper (Refereed)
    Abstract [en]

    Performance analysis of scientific parallel applications is essential to use High Performance Computing (HPC) infrastructures efficiently. Nevertheless, collecting detailed data of large-scale parallel programs and long-running applications is infeasible due to the huge amount of performance information generated. Even though there are no technological constraints in storing Terabytes of performance data, the constant flushing of such data to disk introduces a massive overhead into the application that makes the performance measurements worthless. This paper explores the use of Event flow graphs together with wavelet analysis and EZW-encoding to provide MPI event traces that are orders of magnitude smaller while preserving accurate information on timestamped events. Our mechanism compresses the performance data online while the application runs, thus, reducing the pressure put on the I/O system due to buffer flushing. As a result, we achieve lower application perturbation, reduced performance data output, and the possibility to monitor longer application runs. © The Authors. Published by Elsevier B.V.

  • 2.
    Ahmed, Laeeq
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Edlund, Åke
    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).
    Whitmarsh, S.
    Parallel real time seizure detection in large EEG data2016In: IoTBD 2016 - Proceedings of the International Conference on Internet of Things and Big Data, SciTePress, 2016, p. 214-222Conference paper (Refereed)
    Abstract [en]

    Electroencephalography (EEG) is one of the main techniques for detecting and diagnosing epileptic seizures. Due to the large size of EEG data in long term clinical monitoring and the complex nature of epileptic seizures, seizure detection is both data-intensive and compute-intensive. Analysing EEG data for detecting seizures in real time has many applications, e.g., in automatic seizure detection or in allowing a timely alarm signal to be presented to the patient. In real time seizure detection, seizures have to be detected with negligible delay, thus requiring lightweight algorithms. MapReduce and its variations have been effectively used for data analysis in large dataset problems on general-purpose machines. In this study, we propose a parallel lightweight algorithm for epileptic seizure detection using Spark Streaming. Our algorithm not only classifies seizures in real time, it also learns an epileptic threshold in real time. We furthermore present "top-k amplitude measure" as a feature for classifying seizures in the EEG, that additionally assists in reducing data size. In a benchmark experiment we show that our algorithm can detect seizures in real time with low latency, while maintaining a good seizure detection rate. In short, our algorithm provides new possibilities in using private cloud infrastructures for real time epileptic seizure detection in EEG data.

  • 3. Akhmetova, D.
    et al.
    Kestor, G.
    Gioiosa, R.
    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).
    On the application task granularity and the interplay with the scheduling overhead in many-core shared memory systems2015In: Proceedings - IEEE International Conference on Cluster Computing, ICCC, IEEE , 2015, p. 428-437Conference paper (Refereed)
    Abstract [en]

    Task-based programming models are considered one of the most promising programming model approaches for exascale supercomputers because of their ability to dynamically react to changing conditions and reassign work to processing elements. One question, however, remains unsolved: what should the task granularity of task-based applications be? Fine-grained tasks offer more opportunities to balance the system and generally result in higher system utilization. However, they also induce in large scheduling overhead. The impact of scheduling overhead on coarse-grained tasks is lower, but large systems may result imbalanced and underutilized. In this work we propose a methodology to analyze the interplay between application task granularity and scheduling overhead. Our methodology is based on three main points: 1) a novel task algorithm that analyzes an application directed acyclic graph (DAG) and aggregates tasks, 2) a fast and precise emulator to analyze the application behavior on systems with up to 1,024 cores, 3) a comprehensive sensitivity analysis of application performance and scheduling overhead breakdown. Our results show that there is an optimal task granularity between 1.2x10^4 and 10x10^4 cycles for the representative schedulers. Moreover, our analysis indicates that a suitable scheduler for exascale task-based applications should employ a best-effort local scheduler and a sophisticated remote scheduler to move tasks across worker threads.

  • 4.
    Akhmetova, Dana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Iakymchuk, Roman
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Ekeberg, Örjan
    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).
    Performance study of multithreaded MPI and Openmp tasking in a large scientific code2017In: Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 756-765, article id 7965119Conference paper (Refereed)
    Abstract [en]

    With a large variety and complexity of existing HPC machines and uncertainty regarding exact future Exascale hardware, it is not clear whether existing parallel scientific codes will perform well on future Exascale systems: they can be largely modified or even completely rewritten from scratch. Therefore, now it is important to ensure that software is ready for Exascale computing and will utilize all Exascale resources well. Many parallel programming models try to take into account all possible hardware features and nuances. However, the HPC community does not yet have a precise answer whether, for Exascale computing, there should be a natural evolution of existing models interoperable with each other or it should be a disruptive approach. Here, we focus on the first option, particularly on a practical assessment of how some parallel programming models can coexist with each other. This work describes two API combination scenarios on the example of iPIC3D [26], an implicit Particle-in-Cell code for space weather applications written in C++ and MPI plus OpenMP. The first scenario is to enable multiple OpenMP threads call MPI functions simultaneously, with no restrictions, using an MPI THREAD MULTIPLE thread safety level. The second scenario is to utilize the OpenMP tasking model on top of the first scenario. The paper reports a step-by-step methodology and experience with these API combinations in iPIC3D; provides the scaling tests for these implementations with up to 2048 physical cores; discusses occurred interoperability issues; and provides suggestions to programmers and scientists who may adopt these API combinations in their own codes.

  • 5.
    Ali, Raja Hashim
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    From genomes to post-processing of Bayesian inference of phylogeny2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Life is extremely complex and amazingly diverse; it has taken billions of years of evolution to attain the level of complexity we observe in nature now and ranges from single-celled prokaryotes to multi-cellular human beings. With availability of molecular sequence data, algorithms inferring homology and gene families have emerged and similarity in gene content between two genes has been the major signal utilized for homology inference. Recently there has been a significant rise in number of species with fully sequenced genome, which provides an opportunity to investigate and infer homologs with greater accuracy and in a more informed way. Phylogeny analysis explains the relationship between member genes of a gene family in a simple, graphical and plausible way using a tree representation. Bayesian phylogenetic inference is a probabilistic method used to infer gene phylogenies and posteriors of other evolutionary parameters. Markov chain Monte Carlo (MCMC) algorithm, in particular using Metropolis-Hastings sampling scheme, is the most commonly employed algorithm to determine evolutionary history of genes. There are many softwares available that process results from each MCMC run, and explore the parameter posterior but there is a need for interactive software that can analyse both discrete and real-valued parameters, and which has convergence assessment and burnin estimation diagnostics specifically designed for Bayesian phylogenetic inference.

    In this thesis, a synteny-aware approach for gene homology inference, called GenFamClust (GFC), is proposed that uses gene content and gene order conservation to infer homology. The feature which distinguishes GFC from earlier homology inference methods is that local synteny has been combined with gene similarity to infer homologs, without inferring homologous regions. GFC was validated for accuracy on a simulated dataset. Gene families were computed by applying clustering algorithms on homologs inferred from GFC, and compared for accuracy, dependence and similarity with gene families inferred from other popular gene family inference methods on a eukaryotic dataset. Gene families in fungi obtained from GFC were evaluated against pillars from Yeast Gene Order Browser. Genome-wide gene families for some eukaryotic species are computed using this approach.

    Another topic focused in this thesis is the processing of MCMC traces for Bayesian phylogenetics inference. We introduce a new software VMCMC which simplifies post-processing of MCMC traces. VMCMC can be used both as a GUI-based application and as a convenient command-line tool. VMCMC supports interactive exploration, is suitable for automated pipelines and can handle both real-valued and discrete parameters observed in a MCMC trace. We propose and implement joint burnin estimators that are specifically applicable to Bayesian phylogenetics inference. These methods have been compared for similarity with some other popular convergence diagnostics. We show that Bayesian phylogenetic inference and VMCMC can be applied to infer valuable evolutionary information for a biological case – the evolutionary history of FERM domain.

  • 6.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Arvestad, Lars
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Burnin estimation and convergence assessment in Bayesian phylogenetic inferenceManuscript (preprint) (Other academic)
    Abstract [en]

     Convergence assessment and burnin estimation are central concepts in Markov chain Monte Carlo algorithms. Studies on eects, statistical properties, and comparisons between dierent convergence assessment methods have been conducted during the past few decades. However, not much work has been done on the eect of convergence diagnostic on posterior distribution of tree parameters and which method should be used by researchers in Bayesian phylogenetics inference. In this study, we propose and evaluate two novel burnin estimation methods that estimate burnin using all parameters jointly. We also consider some other popular convergence diagnostics, evaluate them in light of parallel chains and quantify the eect of burnin estimates from various convergence diagnostics on the posterior distribution of trees. We motivate the use of convergence diagnostics to assess convergence and estimate burnin in Bayesian phylogenetics inference and found out that it is better to employ convergence diagnostics rather than remove a xed percentage as burnin. We concluded that the last burnin estimator using eective sample size appears to estimate burnin better than all other convergence diagnostics.

  • 7.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Bark, Mikael
    KTH, School of Information and Communication Technology (ICT).
    Miro, Jorge
    KTH, School of Information and Communication Technology (ICT).
    Muhammad, Sayyed Auwn
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Sjöstrand, Joel
    Stockholm University.
    Zubair, Syed Muhammad
    KTH, School of Electrical Engineering (EES), Communication Networks. University of Balochistan, Pakistan.
    Abbas, Raja Manzar
    Arvestad, Lars
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo tracesManuscript (preprint) (Other academic)
    Abstract [en]

    Motivation: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical diculties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters.

    Results: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines.

    Availability: VMCMC is available for Java SE 6+ under the New BSD License. Executable jar les, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/.

  • 8.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, Centres, SeRC - Swedish e-Science Research Centre.
    Bark, Mikael
    KTH, School of Information and Communication Technology (ICT).
    Miró, Jorge
    KTH, School of Information and Communication Technology (ICT).
    Muhammad, Sayyed Auwn
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, Centres, SeRC - Swedish e-Science Research Centre.
    Sjöstrand, J.
    Zubair, Syed M.
    KTH, School of Electrical Engineering (EES), Communication Networks. University of Balochistan, Pakistan.
    Abbas, R. M.
    Arvestad, L.
    VMCMC: A graphical and statistical analysis tool for Markov chain Monte Carlo traces2017In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 18, no 1, article id 97Article in journal (Refereed)
    Abstract [en]

    Background: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters. Results: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines. Conclusions: VMCMC is a free software available under the New BSD License. Executable jar files, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/.

  • 9.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Muhammad, Sayyed Auwn
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Arvestad, Lars
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    GenFamClust: An accurate, synteny-aware and reliable homology inference algorithm2016In: BMC EVOLUTIONARY BIOLOGY, ISSN 1471-2148, Vol. 16Article in journal (Other academic)
    Abstract [en]

    Background: Homology inference is pivotal to evolutionary biology and is primarily based on significant sequence similarity, which, in general, is a good indicator of homology. Algorithms have also been designed to utilize conservation in gene order as an indication of homologous regions. We have developed GenFamClust, a method based on quantification of both gene order conservation and sequence similarity. Results: In this study, we validate GenFamClust by comparing it to well known homology inference algorithms on a synthetic dataset. We applied several popular clustering algorithms on homologs inferred by GenFamClust and other algorithms on a metazoan dataset and studied the outcomes. Accuracy, similarity, dependence, and other characteristics were investigated for gene families yielded by the clustering algorithms. GenFamClust was also applied to genes from a set of complete fungal genomes and gene families were inferred using clustering. The resulting gene families were compared with a manually curated gold standard of pillars from the Yeast Gene Order Browser. We found that the gene-order component of GenFamClust is simple, yet biologically realistic, and captures local synteny information for homologs. Conclusions: The study shows that GenFamClust is a more accurate, informed, and comprehensive pipeline to infer homologs and gene families than other commonly used homology and gene-family inference methods.

  • 10.
    Ardestani, Shahrzad
    et al.
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.
    Håkansson, Carl Johan
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.
    Laure, Erwin
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.
    Livenson, I.
    Stranak, P.
    Dima, E.
    Blommesteijn, D.
    Van De Sanden, M.
    B2SHARE: An open eScience data sharing platform2015In: Proceedings - 11th IEEE International Conference on eScience, IEEE , 2015, p. 448-453Conference paper (Refereed)
    Abstract [en]

    Scientific data sharing is becoming an essential service for data driven science and can significantly improve the scientific process by making reliable, and trustworthy data available. Thereby reducing redundant work, and providing insights on related research and recent advancements. For data sharing services to be useful in the scientific process, they need to fulfill a number of requirements that cover not only discovery, and access to data. But to ensure the integrity, and reliability of published data as well. B2SHARE, developed by the EUDAT project, provides such a data sharing service to scientific communities. For communities that wish to download, install and maintain their own service, it is also available as software. B2SHARE is developed with a focus on user-friendliness, reliability, and trustworthiness, and can be customized for different organizations and use-cases. In this paper we discuss the design, architecture, and implementation of B2SHARE. We show its usefulness in the scientific process with some case studies in the biodiversity field.

  • 11.
    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.

  • 12.
    Aurell, Erik
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Aalto Univ, Finland.
    The Maximum Entropy Fallacy Redux?2016In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, no 5, article id e1004777Article in journal (Refereed)
  • 13.
    Aurell, Erik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Bo, Stefano
    Dias, Marcelo
    Eichhorn, Ralf
    Marino, Raffaele
    Diffusion of a Brownian ellipsoid in a force field2016In: Europhysics letters, ISSN 0295-5075, E-ISSN 1286-4854, Vol. 114, no 3, article id 30005Article in journal (Refereed)
    Abstract [en]

    We calculate the effective long-term convective velocity and dispersive motion of an ellipsoidal Brownian particle in three dimensions when it is subjected to a constant external force. This long-term motion results as a "net" average behavior from the particle rotation and translation on short time scales. Accordingly, we apply a systematic multi-scale technique to derive the effective equations of motion valid on long times. We verify our theoretical results by comparing them to numerical simulations.

  • 14.
    Aurell, Erik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Del Ferraro, Gino
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    A Cavity Master Equation for the continuous time dynamics of discrete spins modelsManuscript (preprint) (Other academic)
    Abstract [en]

    We present a new method to close the Master Equation representing the continuous time dynamics of Ising interacting spins. The method makes use of the the theory of Random Point Processes to derive a master equation for local conditional probabilities. We analytically test our solution studying two known cases, the dynamics of the mean field ferromagnet and the dynamics of the one dimensional Ising system. We then present numerical results comparing our predictions with Monte Carlo simulations in three different models on random graphs with finite connectivity: the Ising ferromagnet, the Random Field Ising model, and the Viana-Bray spin-glass model.

  • 15.
    Aurell, Erik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Depts of Information and Computer Science and Applied Physics, Aalto University, Finland.
    Del Ferraro, Gino
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Causal analysis, Correlation-Response, and Dynamic cavity2016In: International Meeting on High-Dimensional Data-Driven Science (HD3-2015), Institute of Physics (IOP), 2016, article id 012002Conference paper (Refereed)
    Abstract [en]

    The purpose of this note is to point out analogies between causal analysis in statistics and the correlation-response theory in statistical physics. It is further shown that for some systems the dynamic cavity offers a way to compute the stationary state of a non-equilibrium process effectively, which could then be taken an alternative starting point of causal analysis.

  • 16.
    Aurell, Erik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Aalto University, Finland.
    Innocenti, Nicolas
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). The Hebrew University of Jerusalem, Israel.
    Zhou, Hai-Jun
    State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China.
    The bulk and the tail of minimal absent words in genome sequences2016In: Physical Biology, ISSN 1478-3967, E-ISSN 1478-3975, Vol. 13, no 2, article id 026004Article in journal (Refereed)
    Abstract [en]

    Minimal absent words (MAW) of a genomic sequence are subsequences that are absent themselves but the subwords of which are all present in the sequence. The characteristic distribution of genomic MAWs as a function of their length has been observed to be qualitatively similar for all living organisms, the bulk being rather short, and only relatively few being long. It has been an open issue whether the reason behind this phenomenon is statistical or reflects a biological mechanism, and what biological information is contained in absent words. % In this work we demonstrate that the bulk can be described by a probabilistic model of sampling words from random sequences, while the tail of long MAWs is of biological origin. We introduce the novel concept of a core of a minimal absent word, which are sequences present in the genome and closest to a given MAW. We show that in bacteria and yeast the cores of the longest MAWs, which exist in two or more copies, are located in highly conserved regions the most prominent example being ribosomal RNAs (rRNAs). We also show that while the distribution of the cores of long MAWs is roughly uniform over these genomes on a coarse-grained level, on a more detailed level it is strongly enhanced in 3' untranslated regions (UTRs) and, to a lesser extent, also in 5' UTRs. This indicates that MAWs and associated MAW cores correspond to fine-tuned evolutionary relationships, and suggest that they can be more widely used as markers for genomic complexity.

  • 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.
    Bahuguna, Jyotika
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Structure-Dynamics relationship in basalganglia: Implications for brain function2016Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In this thesis, I have used a combination of computational models such as mean field and spikingnetwork simulations to study various sub-circuits of basal ganglia. I first studied the striatum(chapter 2), which is the input nucleus of basal ganglia. The two types of Medium SpinyNeurons (MSNs), D1 and D2-MSNs, together constitute 98% of the neurons in striatum. Thecomputational models so far have treated striatum as a homogenous unit and D1 and D2 MSNs asinterchangeable subpopulations. This implied that a bias in a Go/No-Go decision is enforced viaexternal agents to the striatum (eg. cortico-striatal weights), thereby assigning it a passive role.New data shows that there is an inherent asymmetry in striatal circuits. In this work, I showedthat striatum due to its asymmetric connectivity acts as a decision transition threshold devicefor the incoming cortical input. This has significant implications on the function of striatum asan active participant in influencing the bias towards a Go/No-Go decision. The striatal decisiontransition threshold also gives mechanistic explanations for phenomena such as L-Dopa InducedDyskinesia (LID), DBS-induced impulsivity, etc. In chapter 3, I extend the mean field model toinclude all the nuclei of basal ganglia to specifically study the role of two new subpopulationsfound in GPe (Globus Pallidus Externa). Recent work shows that GPe, also earlier consideredto be a homogenous nucleus, has at least two subpopulations which are dichotomous in theiractivity with respect to the cortical Slow Wave (SWA) and beta activity. Since the data for thesesubpopulations are missing, a parameter search was performed for effective connectivities usingGenetic Algorithms (GA) to fit the available experimental data. One major result of this studyis that there are various parameter combinations that meet the criteria and hence the presenceof functional homologs of the basal ganglia network for both pathological (PD) and healthynetworks is a possibility. Classifying all these homologous networks into clusters using somehigh level features of PD shows a large variance, hinting at the variance observed among the PDpatients as well as their response to the therapeutic measures. In chapter 4, I collaborated on aproject to model the role of STN and GPe burstiness for pathological beta oscillations as seenduring PD. During PD, the burstiness in the firing patterns of GPe and STN neurons are shownto increase. We found that in the baseline state, without any bursty neurons in GPe and STN,the GPe-STN network can transition to an oscillatory state through modulating the firing ratesof STN and GPe neurons. Whereas when GPe neurons are systematically replaced by burstyneurons, we found that increase in GPe burstiness enforces oscillations. An optimal % of burstyneurons in STN destroys oscillations in the GPe-STN network. Hence burstiness in STN mayserve as a compensatory mechanism to destroy oscillations. We also propose that bursting inGPe-STN could serve as a mechanism to initiate and kill oscillations on short time scales, asseen in the healthy state. The GPe-STN network however loses the ability to kill oscillations inthe pathological state.

  • 19. 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.

  • 20. 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.

  • 21. Beerenwinkel, N.
    et al.
    Greenman, C. D.
    Lagergren, Jens
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Computational Cancer Biology: An Evolutionary Perspective2016In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, no 2, article id e1004717Article in journal (Refereed)
  • 22.
    Bekkouche, Bo
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH.
    Classification of Neuronal Subtypes in the Striatum and the Effect of Neuronal Heterogeneity on the Activity Dynamics2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Clustering of single-cell RNA sequencing data is often used to show what states and subtypes cells have. Using this technique, striatal cells were clustered into subtypes using different clustering algorithms. Previously known subtypes were confirmed and new subtypes were found. One of them is a third medium spiny neuron subtype. Using the observed heterogeneity, as a second task, this project questions whether or not differences in individual neurons have an impact on the network dynamics. By clustering spiking activity from a neural network model, inconclusive results were found. Both algorithms indicating low heterogeneity, but by altering the quantity of a subtype between a low and high number, and clustering the network activity in each case, results indicate that there is an increase in the heterogeneity. This project shows a list of potential striatal subtypes and gives reasons to keep giving attention to biologically observed heterogeneity.

  • 23.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Imperial College London, United Kingdom; University of Belgrade, Serbia.
    Faisal, Aldo
    Imperial College London.
    Decoding of human hand actions to handle missing limbs in neuroprosthetics2015In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 9, no 27, p. 1-11Article in journal (Refereed)
    Abstract [en]

    The only way we can interact with the world is through movements, and our primary interactions are via the hands, thus any loss of hand function has immediate impact on our quality of life. However, to date it has not been systematically assessed how coordination in the hand's joints affects every day actions. This is important for two fundamental reasons. Firstly, to understand the representations and computations underlying motor control “in-the-wild” situations, and secondly to develop smarter controllers for prosthetic hands that have the same functionality as natural limbs. In this work we exploit the correlation structure of our hand and finger movements in daily-life. The novelty of our idea is that instead of averaging variability out, we take the view that the structure of variability may contain valuable information about the task being performed. We asked seven subjects to interact in 17 daily-life situations, and quantified behavior in a principled manner using CyberGlove body sensor networks that, after accurate calibration, track all major joints of the hand. Our key findings are: (1) We confirmed that hand control in daily-life tasks is very low-dimensional, with four to five dimensions being sufficient to explain 80–90% of the variability in the natural movement data. (2) We established a universally applicable measure of manipulative complexity that allowed us to measure and compare limb movements across tasks. We used Bayesian latent variable models to model the low-dimensional structure of finger joint angles in natural actions. (3) This allowed us to build a naïve classifier that within the first 1000 ms of action initiation (from a flat hand start configuration) predicted which of the 17 actions was going to be executed—enabling us to reliably predict the action intention from very short-time-scale initial data, further revealing the foreseeable nature of hand movements for control of neuroprosthetics and tele operation purposes. (4) Using the Expectation-Maximization algorithm on our latent variable model permitted us to reconstruct with high accuracy (<56° MAE) the movement trajectory of missing fingers by simply tracking the remaining fingers. Overall, our results suggest the hypothesis that specific hand actions are orchestrated by the brain in such a way that in the natural tasks of daily-life there is sufficient redundancy and predictability to be directly exploitable for neuroprosthetics.

  • 24.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab. Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.
    Halje, Pär
    Lund University.
    Richter, Ulrike
    Lund University.
    Per, Petersson
    Lund University.
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
    Untangling cortico-striatal connectivity and cross-frequency coupling in L-DOPA-induced dyskinesia2016In: Frontiers in Systems Neuroscience, ISSN 1662-5137, E-ISSN 1662-5137, Vol. 10, no 26, p. 1-12Article in journal (Refereed)
    Abstract [en]

    We simultaneously recorded local field potentials in the primary motor cortex and sensorimotor striatum in awake, freely behaving, 6-OHDA lesioned hemi-parkinsonian rats in order to study the features directly related to pathological states such as parkinsonian state and levodopa-induced dyskinesia. We analysed the spectral characteristics of the obtained signals and observed that during dyskinesia the most prominent feature was a relative power increase in the high gamma frequency range at around 80 Hz, while for the parkinsonian state it was in the beta frequency range. Here we show that during both pathological states effective connectivity in terms of Granger causality is bidirectional with an accent on the striatal influence on the cortex. In the case of dyskinesia, we also found a high increase in effective connectivity at 80 Hz. In order to further understand the 80- Hz phenomenon, we performed cross-frequency analysis and observed characteristic patterns in the case of dyskinesia but not in the case of the parkinsonian state or the healthy state. We noted a large decrease in the modulation of the amplitude at 80 Hz by the phase of low frequency oscillations (up to ~10 Hz) across both structures in the case of dyskinesia. This may suggest a lack of coupling between the low frequency activity of the recorded network and the group of neurons active at ~80 Hz.

  • 25.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Halje, Pär
    Lund University.
    Richter, Ulrike
    Lund University.
    Petersson, Per
    Lund University.
    Hällgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Behavior Discrimination Using a Discrete Wavelet Based Approach for Feature Extraction on Local Field Potentials in the Cortex and Striatum2015In: 7th International IEEE/EMBS Conference on Neural Engineering (NER), IEEE conference proceedings, 2015, Vol. 7, p. 964-967Conference paper (Refereed)
    Abstract [en]

    Linkage between behavioral states and neural activity is one of the most important challenges in neuroscience. The network activity patterns in the awake resting state and in the actively behaving state in rodents are not well understood, and a better tool for differentiating these states can provide insights on healthy brain functions and its alteration with disease. Therefore, we simultaneously recorded local field potentials (LFPs) bilaterally in motor cortex and striatum, and measured locomotion from healthy, freely behaving rats. Here we analyze spectral characteristics of the obtained signals and present an algorithm for automatic discrimination of the awake resting and the behavioral states. We used the Support Vector Machine (SVM) classifier and utilized features obtained by applying discrete wavelet transform (DWT) on LFPs, which arose as a solution with high accuracy.

  • 26.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). University of Freiburg, Germany.
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Karolinska Institute, Sweden.
    Striatal processing of cortical neuronal avalanches – A computational investigation2016In: International Conference on Artificial Neural Networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, 2016, Vol. 9886, p. 72-79Conference paper (Refereed)
    Abstract [en]

    In the cortex, spontaneous neuronal avalanches can be characterized by spatiotemporal activity clusters with a cluster size distribution that follows a power law with exponent –1.5. Recordings in the striatum revealed that striatal activity was also characterized by spatiotemporal clusters that followed a power law distribution albeit, with significantly steeper slope, i.e., they lacked the large spatial clusters that are commonly expected for avalanche dynamics. In this study, we used computational modeling to investigate the influence of intrastriatal inhibition and corticostriatal interplay as important factors to understand the experimental findings and overall information transmission among these circuits.

  • 27.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). University of Freiburg, Germany.
    Klaus, Andreas
    National Institute of Mental Health, Bethesda, USA.
    Plenz, Dietmar
    National Institute of Mental Health, Bethesda, USA.
    Hällgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC).
    Mapping of Cortical Avalanches to the Striatum2015In: Advances in Cognitive Neurodynamics, Springer Netherlands, 2015, 4, p. 291-297Chapter in book (Refereed)
    Abstract [en]

    Neuronal avalanches are found in the resting state activity of the mammaliancortex. Here we studied whether and how cortical avalanches are mappedonto the striatal circuitry, the first stage of the basal ganglia. We first demonstrate using organotypic cortex-striatum-substantia nigra cultures from rat that indeed striatal neurons respond to cortical avalanches originating in superficial layers. We simultaneously recorded spontaneous local field potentials (LFPs) in the cortical and striatal tissue using high-density microelectrode arrays. In the cortex, spontaneous neuronal avalanches were characterized by intermittent spatiotemporal activity clusters with a cluster size distribution that followed a power law with exponent 1.5. In the striatum, intermittent spatiotemporal activity was found to correlate with cortical avalanches. However, striatal negative LFP peaks (nLFPs) did not showavalanche signatures, but formed a cluster size distribution that had a much steeper drop-off, i.e., lacked large spatial clusters that are commonly expected for avalanche dynamics. The underlying de-correlation of striatal activity could have its origin in the striatum through local inhibition and/or could result from a particular mapping in the corticostriatal pathway. Here we show, using modeling, that highly convergent corticostriatal projections can map spatially extended cortical activity into spatially restricted striatal regimes.

  • 28.
    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.

  • 29.
    Belic, Jovana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Savic, Andrej
    University of Belgrade.
    Detecting and comparing the onset of self-paced and cue-based finger movements from EEG signals2015In: 7th Annual International IEEE Conference on Computer Science and Electronic Engineering (CEEC), Colchester, UK: IEEE conference proceedings, 2015, Vol. 7, p. 157-160Conference paper (Refereed)
    Abstract [en]

    We asked four subjects to perform the task of pressing a taster button with their thumbs, while their EEG recordings were obtained, in order to determine the probability of the subjects' intention to make the movement in comparison to the idle state. Humans usually spontaneously decide when to initiate movements to complete daily-life tasks, but sometimes our movements can also be externally triggered. Thus, the subjects first performed motor tasks at the instants defined by the animation shown on the screen and second, the subjects performed self-initiated movements. In this paper, we study if there is a difference in the classification results and coherence measures of EEG signals in these two paradigms. We used the Support Vector Machine (SVM) classifier on features extracted by applying Burg's algorithm to EEG signals, which arose as a solution with high accuracy.

  • 30.
    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.

  • 31.
    Berthet, Pierre
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Karolinska Institute, Stockholm, Sweden.
    Lindahl, Mikael
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Karolinska Institute, Stockholm, Sweden.
    Tully, Philip
    Hällgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Karolinska Institute, Stockholm, Sweden.
    Lansner, Anders
    Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking 1 Model with Reward Dependent PlasticityManuscript (preprint) (Other academic)
  • 32.
    Beskow, Jonas
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Peters, Christopher
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Castellano, G.
    O'Sullivan, C.
    Leite, Iolanda
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
    Kopp, S.
    Preface2017In: 17th International Conference on Intelligent Virtual Agents, IVA 2017, Springer, 2017, Vol. 10498, p. V-VIConference paper (Refereed)
  • 33. Bjorklund, Andreas
    et al.
    Husfeldt, Thore
    Kaski, Petteri
    Koivisto, Mikko
    Nederlof, Jesper
    Parviainen, Pekka
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Aalto University, Finland.
    Fast Zeta Transforms for Lattices with Few Irreducibles2016In: ACM Transactions on Algorithms, ISSN 1549-6325, E-ISSN 1549-6333, Vol. 12, no 1, article id 4Article in journal (Refereed)
    Abstract [en]

    We investigate fast algorithms for changing between the standard basis and an orthogonal basis of idempotents for Mobius algebras of finite lattices. We show that every lattice with v elements, n of which are nonzero and join-irreducible (or, by a dual result, nonzero and meet-irreducible), has arithmetic circuits of size O(vn) for computing the zeta transform and its inverse, thus enabling fast multiplication in the Mobius algebra. Furthermore, the circuit construction in fact gives optimal (up to constants) monotone circuits for several lattices of combinatorial and algebraic relevance, such as the lattice of subsets of a finite set, the lattice of set partitions of a finite set, the lattice of vector subspaces of a finite vector space, and the lattice of positive divisors of a positive integer.

  • 34. 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.

  • 35.
    Brocke, Ekaterina
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Bhalla, Upinder S.
    Djurfeldt, Mikael
    Hällgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hanke, Michael
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).
    Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations2016In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 10, article id 97Article in journal (Refereed)
    Abstract [en]

    Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience.

  • 36.
    Brocke, Ekaterina
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Djurfeldt, M.
    Bhalla, U. S.
    Hellgren Kotaleski, Jeanette
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Hanke, Michael
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Numerical Analysis, NA.
    Multirate method for co-simulation of electrical-chemical systems in multiscale modeling2017In: Journal of Computational Neuroscience, ISSN 0929-5313, E-ISSN 1573-6873, Vol. 42, no 3, p. 245-256Article in journal (Refereed)
    Abstract [en]

    Multiscale modeling by means of co-simulation is a powerful tool to address many vital questions in neuroscience. It can for example be applied in the study of the process of learning and memory formation in the brain. At the same time the co-simulation technique makes it possible to take advantage of interoperability between existing tools and multi-physics models as well as distributed computing. However, the theoretical basis for multiscale modeling is not sufficiently understood. There is, for example, a need of efficient and accurate numerical methods for time integration. When time constants of model components are different by several orders of magnitude, individual dynamics and mathematical definitions of each component all together impose stability, accuracy and efficiency challenges for the time integrator. Following our numerical investigations in Brocke et al. (Frontiers in Computational Neuroscience, 10, 97, 2016), we present a new multirate algorithm that allows us to handle each component of a large system with a step size appropriate to its time scale. We take care of error estimates in a recursive manner allowing individual components to follow their discretization time course while keeping numerical error within acceptable bounds. The method is developed with an ultimate goal of minimizing the communication between the components. Thus it is especially suitable for co-simulations. Our preliminary results support our confidence that the multirate approach can be used in the class of problems we are interested in. We show that the dynamics ofa communication signal as well as an appropriate choice of the discretization order between system components may have a significant impact on the accuracy of the coupled simulation. Although, the ideas presented in the paper have only been tested on a single model, it is likely that they can be applied to other problems without loss of generality. We believe that this work may significantly contribute to the establishment of a firm theoretical basis and to the development of an efficient computational framework for multiscale modeling and simulations.

  • 37. Capuccini, Marco
    et al.
    Ahmed, Laeeq
    KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Schaal, Wesley
    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).
    Spjuth, Ola
    Large-scale virtual screening on public cloud resources with Apache Spark2017In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 9, article id 15Article in journal (Refereed)
    Abstract [en]

    Background: Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. Results: We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against similar to 2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Conclusion: Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries.

  • 38. Cazzola, E.
    et al.
    Innocenti, M. E.
    Goldman, M. V.
    Newman, D. L.
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lapenta, G.
    Electrons dynamics in asymmetric magnetic reconnection and rapid island coalescence: Anisotropy and agyrotropywith andwithout a guide field2016In: 43rd European Physical Society Conference on Plasma Physics, EPS 2016, European Physical Society (EPS) , 2016Conference paper (Refereed)
  • 39. Cazzola, E.
    et al.
    Innocenti, M. E.
    Goldman, M. V.
    Newman, D. L.
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lapenta, G.
    On the electron agyrotropy during rapid asymmetric magnetic island coalescence in presence of a guide field2016In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 43, no 15, p. 7840-7849Article in journal (Refereed)
    Abstract [en]

    We present an analysis of the properties of the electron velocity distribution during island coalescence in asymmetric reconnection with and without guide field. In a previous study, three main domains were identified, in the case without guide field, as X, D, and M regions featuring different reconnection evolutions. These regions are also identified here in the case with guide field. We study the departure from isotropic and gyrotropic behavior by means of different robust detection algorithms proposed in the literature. While in the case without guide field these metrics show an overall agreement, when the guide field is present, a discrepancy in the agyrotropy within some relevant regions is observed, such as at the separatrices and inside magnetic islands. Moreover, in light of the new observations from the Multiscale MagnetoSpheric mission, an analysis of the electron velocity phase-space in these domains is presented.

  • 40. Choudhari, M.
    et al.
    Lockard, D. P.
    Jenkins,
    Neuhart,
    Choudhari,
    Cattafesta,
    Murayama,
    Yamamoto,
    Ura,
    Ito,
    Vilela de Abreu, Rodrigo
    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).
    Jansson, Johan
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lockard,
    Ueno,
    Knacke,
    Thiele,
    Dahan, Jeremy
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Tamaki,
    Imamura,
    Tanaka,
    Amemiya,
    Hirai,
    Ashton,
    West,
    Mendonca,
    Housman,
    Kiris,
    Ribeiro,
    Fares,
    Casalino,
    Terracol,
    Ewert,
    Boenke,
    Simoes,
    Bonatto,
    Souza,
    Medeiros,
    Bodart,
    Larsson,
    Moin,
    Assessment of slat noise predictions for 30P30N high- lift configuration from Banc-III workshop2015In: 21st AIAA/CEAS Aeroacoustics Conference, American Institute of Aeronautics and Astronautics, 2015Conference paper (Refereed)
    Abstract [en]

    This paper presents a summary of the computational predictions and measurement data contributed to Category 7 of the 3rd AIAA Workshop on Benchmark Problems for Airframe Noise Computations (BANC-III), which was held in Atlanta, GA, on June 14-15, 2014. Category 7 represents the first slat-noise configuration to be investigated under the BANC series of workshops, namely, the 30P30N two-dimensional high-lift model (with a slat contour that was slightly modified to enable unsteady pressure measurements) at an angle of attack that is relevant to approach conditions. Originally developed for a CFD challenge workshop to assess computational fluid dynamics techniques for steady high-lift predictions, the 30P30N configurations has provided a valuable opportunity for the airframe noise community to collectively assess and advance the computational and experimental techniques for slat noise. The contributed solutions are compared with each other as well as with the initial measurements that became available just prior to the BANC-III Workshop. Specific features of a number of computational solutions on the finer grids compare reasonably well with the initial measurements from FSU and JAXA facilities and/or with each other. However, no single solution (or a subset of solutions) could be identified as clearly superior to the remaining solutions. Grid sensitivity studies presented by multiple BANC-III participants demonstrated a relatively consistent trend of reduced surface pressure fluctuations, higher levels of turbulent kinetic energy in the flow, and lower levels of both narrow band peaks and the broadband component of unsteady pressure spectra in the nearfield and farfield. The lessons learned from the BANC-III contributions have been used to identify improvements to the problem statement for future Category-7 investigations.

  • 41. Corrigan, L. J.
    et al.
    Peters, Christopher
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Küster, D.
    Castellano, G.
    Engagement perception and generation for social robots and virtual agents2016In: Toward Robotic Socially Believable Behaving Systems - Volume I, Springer Science+Business Media B.V., 2016, p. 29-51Chapter in book (Refereed)
    Abstract [en]

    Technology is the future, woven into every aspect of our lives, but how are we to interact with all this technology and what happens when problems arise? Artificial agents, such as virtual characters and social robots could offer a realistic solution to help facilitate interactions between humans and machines—if only these agents were better equipped and more informed to hold up their end of an interaction. People and machines can interact to do things together, but in order to get the most out of every interaction, the agent must to be able to make reasonable judgements regarding your intent and goals for the interaction.We explore the concept of engagement from the different perspectives of the human and the agent. More specifically, we study how the agent perceives the engagement state of the other interactant, and how it generates its own representation of engaging behaviour. In this chapter, we discuss the different stages and components of engagement that have been suggested in the literature from the applied perspective of a case study of engagement for social robotics, as well as in the context of another study that was focused on gaze-related engagement with virtual characters.

  • 42.
    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.

  • 43. 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.

  • 44. Deca, Jan
    et al.
    Divin, Andrey
    Wang, Xu
    Lembege, Bertrand
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).
    Horanyi, Mihaly
    Lapenta, Giovanni
    Three-dimensional full-kinetic simulation of the solar wind interaction with a vertical dipolar lunarmagnetic anomaly2016In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 43, no 9, p. 4136-4144Article in journal (Refereed)
    Abstract [en]

    A detailed understanding of the solar wind interaction with lunar magnetic anomalies (LMAs) is essential to identify its implications for lunar exploration and to enhance our physical understanding of the particle dynamics in a magnetized plasma. We present the first three-dimensional full-kinetic electromagnetic simulation case study of the solar wind interaction with a vertical dipole, resembling a medium-size LMA. In contrast to a horizontal dipole, we show that a vertical dipole twists its field lines and cannot form a minimagnetosphere. Instead, it creates a ring-shaped weathering pattern and reflects up to 21% (four times more as compared to the horizontal case) of the incoming solar wind ions electrostatically through the normal electric field formed above the electron shielding region surrounding the cusp. This work delivers a vital piece to fully comprehend and interpret lunar observations, as we find the amount of reflected ions to be a tracer for the underlying field structure.

  • 45.
    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.

  • 46.
    Del Ferraro, Gino
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Equilibrium and Dynamics on Complex Networkds2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Complex networks are an important class of models used to describe the behaviour of a very broad category of systems which appear in different fields of science ranging from physics, biology and statistics to computer science and other disciplines. This set of models includes spin systems on a graph, neural networks, decision networks, spreading disease, financial trade, social networks and all systems which can be represented as interacting agents on some sort of graph architecture.

    In this thesis, by using the theoretical framework of statistical mechanics, the equilibrium and the dynamical behaviour of such systems is studied.

    For the equilibrium case, after presenting the region graph free energy approximation, the Survey Propagation method, previously used to investi- gate the low temperature phase of complex systems on tree-like topologies, is extended to the case of loopy graph architectures.

    For time-dependent behaviour, both discrete-time and continuous-time dynamics are considered. It is shown how to extend the cavity method ap- proach from a tool used to study equilibrium properties of complex systems to the discrete-time dynamical scenario. A closure scheme of the dynamic message-passing equation based on a Markovian approximations is presented. This allows to estimate non-equilibrium marginals of spin models on a graph with reversible dynamics. As an alternative to this approach, an extension of region graph variational free energy approximations to the non-equilibrium case is also presented. Non-equilibrium functionals that, when minimized with constraints, lead to approximate equations for out-of-equilibrium marginals of general spin models are introduced and discussed.

    For the continuous-time dynamics a novel approach that extends the cav- ity method also to this case is discussed. The main result of this part is a Cavity Master Equation which, together with an approximate version of the Master Equation, constitutes a closure scheme to estimate non-equilibrium marginals of continuous-time spin models. The investigation of dynamics of spin systems is concluded by applying a quasi-equilibrium approach to a sim- ple case. A way to test self-consistently the assumptions of the method as well as its limits is discussed.

    In the final part of the thesis, analogies and differences between the graph- ical model approaches discussed in the manuscript and causal analysis in statistics are presented.

  • 47.
    Del Ferraro, Gino
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Aurell, Erik
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Aalto University, Finland.
    Dynamic message-passing approach for kinetic spin models with reversible dynamics2015In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, ISSN 1539-3755, E-ISSN 1550-2376, Vol. 92, no 1, article id 010102Article in journal (Refereed)
    Abstract [en]

    A method to approximately close the dynamic cavity equations for synchronous reversible dynamics on a locally treelike topology is presented. The method builds on (a) a graph expansion to eliminate loops from the normalizations of each step in the dynamics and (b) an assumption that a set of auxilary probability distributions on histories of pairs of spins mainly have dependencies that are local in time. The closure is then effectuated by projecting these probability distributions on n-step Markov processes. The method is shown in detail on the level of ordinary Markov processes (n = 1) and outlined for higher-order approximations (n > 1). Numerical validations of the technique are provided for the reconstruction of the transient and equilibrium dynamics of the kinetic Ising model on a random graph with arbitrary connectivity symmetry.

  • 48.
    Del Ferraro, Gino
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Wang, Chuang
    Martì, Dani
    Mézard, Marc
    Cavity Method: Message Passing from a Physics perspective2016In: Statistical Physics, Optimization, Inference, and Message-Passing Algorithms: Lecture Notes of the Les Houches School of Physics - Special Issue October 2013 / [ed] F. Krzakala et al., Oxford University Press, 2016Chapter in book (Other academic)
    Abstract [en]

    In this three-sections lecture cavity method is introduced as heuristic framework from a Physics perspective to solve probabilistic graphical models and it is presented both at the replica symmetric (RS) and 1-step replica symmetry breaking (1RSB) level. This technique has been applied with success on a wide range of models and problems such as spin glasses, random constrain satisfaction problems (rCSP), error correcting codes etc. Firstly, the RS cavity solution for Sherrington-Kirkpatrick model---a fully connected spin glass model---is derived and its equivalence to the RS solution obtained using replicas is discussed. Then, the general cavity method for diluted graphs is illustrated both at RS and 1RSB level. The latter was a significant breakthrough in the last decade and has direct applications to rCSP. Finally, as example of an actual problem, K-SAT is investigated using belief and survey propagation.

  • 49. Divin, A.
    et al.
    Khotyaintsev, Y. V.
    Vaivads, A.
    André, M.
    Toledo-Redondo, S.
    Markidis, Stefano
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Lapenta, G.
    Three-scale structure of diffusion region in the presence of cold ions2016In: Journal of Geophysical Research - Space Physics, ISSN 2169-9380, E-ISSN 2169-9402, Vol. 121, no 12, p. 12,001-12,013Article in journal (Refereed)
    Abstract [en]

    Kinetic simulations and spacecraft observations typically display the two-scale structure of collisionless diffusion region (DR), with electron and ion demagnetization scales governing the spatial extent of the DR. Recent in situ observations of the nightside magnetosphere, as well as investigation of magnetic reconnection events at the Earth's magnetopause, discovered the presence of a population of cold (tens of eV) ions of ionospheric origin. We present two-dimensional particle-in-cell simulations of collisionless magnetic reconnection in multicomponent plasma with ions consisting of hot and cold populations. We show that a new cold ion diffusion region scale is introduced in between that of hot ions and electrons. Demagnetization scale of cold ion population is several times (∼4–8) larger than the initial cold ion gyroradius. Cold ions are accelerated and thermalized during magnetic reconnection and form ion beams moving with velocities close to the Alfvén velocity.

  • 50.
    Ekeberg, Örjan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Fransén, Erik
    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).
    Herman, Pawel
    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).
    Lansner, Anders
    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).
    Computational Brain Science at CST, CSC, KTH2016Other (Other academic)
    Abstract [en]

    Mission and Vision - Computational Brain Science Lab at CST, CSC, KTH

    The scientific mission of the Computational Brain Science Lab at CSC is to be at the forefront of mathematical modelling, quantitative analysis and mechanistic understanding of brain function. We perform research on (i) computational modelling of biological brain function and on (ii) developing theory, algorithms and software for building computer systems that can perform brain-like functions. Our research answers scientific questions and develops methods in these fields. We integrate results from our science-driven brain research into our work on brain-like algorithms and likewise use theoretical results about artificial brain-like functions as hypotheses for biological brain research.

    Our research on biological brain function includes sensory perception (vision, hearing, olfaction, pain), cognition (action selection, memory, learning) and motor control at different levels of biological detail (molecular, cellular, network) and mathematical/functional description. Methods development for investigating biological brain function and its dynamics as well as dysfunction comprises biomechanical simulation engines for locomotion and voice, machine learning methods for analysing functional brain images, craniofacial morphology and neuronal multi-scale simulations. Projects are conducted in close collaborations with Karolinska Institutet and Karolinska Hospital in Sweden as well as other laboratories in Europe, U.S., Japan and India.

    Our research on brain-like computing concerns methods development for perceptual systems that extract information from sensory signals (images, video and audio), analysis of functional brain images and EEG data, learning for autonomous agents as well as development of computational architectures (both software and hardware) for neural information processing. Our brain-inspired approach to computing also applies more generically to other computer science problems such as pattern recognition, data analysis and intelligent systems. Recent industrial collaborations include analysis of patient brain data with MentisCura and the startup company 13 Lab bought by Facebook.

    Our long term vision is to contribute to (i) deeper understanding of the computational mechanisms underlying biological brain function and (ii) better theories, methods and algorithms for perceptual and intelligent systems that perform artificial brain-like functions by (iii) performing interdisciplinary and cross-fertilizing research on both biological and artificial brain-like functions. 

    On one hand, biological brains provide existence proofs for guiding our research on artificial perceptual and intelligent systems. On the other hand, applying Richard Feynman’s famous statement ”What I cannot create I do not understand” to brain science implies that we can only claim to fully understand the computational mechanisms underlying biological brain function if we can build and implement corresponding computational mechanisms on a computerized system that performs similar brain-like functions.

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