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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Clustering analysis for the management of self-monitoring device networks

Clustering analysis for the management of self-monitoring de...

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5th International Conference on Autonomic Computing, ICAC 2008

作者： Quiroz, Andres Parashar, Manish Gnanasambandam, Nathan Sharma, Naveen CAIP Center Rutgers University Applied Software Systems Laboratory Piscataway NJ United States Xerox Research Webster NY United States

ISBN: (纸本)9780769531755

The increasing computing and communication capabilities of multi-function devices (MFDs) have enabled networks of such devices to provide value-added services. This has placed stringent QoS requirements on the operations of these device networks. This paper investigates how the computational capabilities of the devices in the network can be harnessed to achieve self-monitoring and QoS management. Specifically, the paper investigates the application of clustering analysis for detecting anomalies and trends in events generated during device operation, and presents a novel decentralized cluster and anomaly detection algorithm. The paper also describes how the algorithm can be implemented within a device overlay network, and demonstrates its performance and utility using simulated as well as real workloads. © 2008 IEEE.

关键词： Quality of service

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Clustering Analysis for the Management of Self-Monitoring Device Networks

Clustering Analysis for the Management of Self-Monitoring De...

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International Conference on Autonomic Computing (ICAC)

作者： Andres Quiroz Manish Parashar Nathan Gnanasambandam Naveen Sharma CAIP Center The Applied Software Systems Laboratory Rutgers University Piscataway NJ USA Xerox Research Webster NY USA

关键词： Computer networks Data analysis Computer network management Monitoring Event detection Clustering algorithms Storage automation Conference management software systems Laboratories

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Autonomic proactive runtime partitioning strategies for SAMR applications

Autonomic proactive runtime partitioning strategies for SAMR...

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Proceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)

作者： Zhang, Yeliang Yang, Jingmei Hariri, Salim Chandra, Sumir Parashar, Manish HPDC Laboratory University of Arizona Applied Software Systems Laboratory ECE/CAIP Rutgers University

ISBN: (纸本)0769521320

Dynamic structured adaptive mesh refinement (SAMR) techniques along with the emergence of the computational Grid offer the potential for realistic scientific and engineering simulations of complex physical phenomena. However, the inherent dynamic nature of SAMR applications coupled with the heterogeneity and dynamism of the underlying Grid environment present significant research challenges. This paper presents proactive runtime partitioning strategies based on performance prediction functions that are experimentally formulated in terms of system parameters such as CPU load and available memory. These proactive partitioning strategies form a part of the GridARM autonomic framework which enables self-managing, self-adapting, and self-optimizing SAMR applications on the Grid. Experimental evaluation of the proactive schemes using the 3-D Richtmyer-Meshkov compressible fluid dynamics kernel for different system configurations and workloads demonstrates the improvement in overall runtime performance.

关键词： Adaptive systems

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Autonomic proactive runtime partitioning strategies for SAMR applications

Autonomic proactive runtime partitioning strategies for SAMR...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： S. Chandra M. Parashar Y. Zhang J. Yang S. Hariri HPDC Laboratory University of Arizona Tucson USA Applied Software Systems Laboratory ECE/CAIP Rutgers University USA

Summary form only given. Dynamic structured adaptive mesh refinement (SAMR) techniques along with the emergence of the computational grid offer the potential for realistic scientific and engineering simulations of complex physical phenomena. However, the inherent dynamic nature of SAMR applications coupled with the heterogeneity and dynamism of the underlying grid environment present significant research challenges. We present proactive runtime partitioning strategies based on performance prediction functions that are experimentally formulated in terms of system parameters such as CPU load and available memory. These proactive partitioning strategies form a part of the GridARM autonomic framework which enables self-managing, self-adapting, and self-optimizing SAMR applications on the grid. Experimental evaluation of the proactive schemes using the 3D Richtmyer-Meshkov compressible fluid dynamics kernel for different system configurations and workloads demonstrates the improvement in overall runtime performance.

关键词： Runtime Grid computing Computational modeling Application software Laboratories Adaptive mesh refinement Physics computing Fluid dynamics Kernel software systems

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Online monitoring and analysis for self-protection against network attacks

Online monitoring and analysis for self-protection against n...

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International Conference on Autonomic Computing (ICAC)

作者： Guangzhi Qu S. Hariri S. Jangiti J. Rudraraju Seungchan Oh S. Fayssal Guangsen Zhang M. Parashar Internet Technology Laboratory University of Arizona Tucson USA The Applied Software Systems Laboratory ECE/CAIP Rutgers University USA

In this paper, we present an online monitoring and analysis framework to achieve self-protection against a wide range of network attacks. Our approach uses the software agents to online monitor several attributes to characterize the state of any network or computing resource as normal, uncertain, or abnormal. The software agents execute the appropriate recovery mechanisms once they determine that a service, and/or a network device is operating abnormally. We have developed a test bed to demonstrate and validate our approach to protect against several well-known attacks.

关键词： Monitoring software agents Computer networks Protection Laboratories IP networks software systems Testing Fault trees System software

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Adaptive QoS management for collaboration in heterogeneous environments 16

Adaptive QoS management for collaboration in heterogeneous e...

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16th International Parallel and Distributed Processing Symposium, IPDPS 2002

作者： Chowdhury, R. Bhandarkar, P. Parashar, M. Applied Software Systems Laboratory Department of Electrical and Computer Engineering CAIP Center Rutgers the State University of New Jersey 94 Brett Road PiscatawayNJ08854 United States

ISBN: (纸本)0769515738

Adaptive Quality-of-Service management is critical for enabling effective collaboration between distributed clients in a heterogeneous (wired and wireless) environment. This is because both client profiles (capabilities, interests and resources) and system resources can be significantly different and highly dynamic. This paper presents the design and prototype implementation of an adaptive QoS management framework for collaborative multimedia applications in distributed, heterogeneous environments. The overall goal of the framework is to locally adapt the shared information to meet the capabilities, interests and current state of each collaborating client while preserving the semantic content of the information to maintain effective sharing. Transformations investigated in this paper include gradual gradations and modality transformations. The framework builds on a publisher-subscriber messaging substrate that uses semantic profiles and provides each client with direct and immediate access to all information defined by its needs and capabilities, without having to maintain and update global rosters. It interfaces with the Simple Network Management Protocol (SNMP) to determine the state of the network by directly querying network elements. An experimental evaluation of the framework for wired and wireless clients is also presented. © 2002 IEEE.

关键词： Adaptive QoS management collaboration heterogeneity multimedia network management publisher-subscriber paradigm

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Adaptive QoS management for collaboration in heterogeneous environments

Adaptive QoS management for collaboration in heterogeneous e...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： R. Chowdhury P. Bhandarkar M. Parashar The Applied Software Systems Laboratory Department of Electrical and Computer Engineering & CAIP Center Rutgers State University of New Jersey Piscataway NJ USA

关键词： Environmental management Collaboration Collaborative work Computer networks software systems Quality of service Quality management Engineering management Collaborative software Prototypes

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System sensitive runtime management of adaptive applications 15

System sensitive runtime management of adaptive applications

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15th International Parallel and Distributed Processing Symposium, IPDPS 2001

作者： Sinha, S. Parashar, M. Applied Software Systems Laboratory ECE/CAIP Rutgers The State University of New Jersey PiscatawayNJ08855-8060 United States

ISBN: (纸本)0769509908

This paper presents the design and evaluation of a system sensitive partitioning and load balancing framework for distributed adaptive grid hierarchies that underlie parallel adaptive mesh-refinement (AMR) techniques for the solution of partial-differential equations. The framework uses system capabilities and current system state to select and tune appropriate distribution parameters (e.g. partitioning granularity, load per processor) to maximize overall application performance. © 2001 IEEE.

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System sensitive runtime management of adaptive applications

System sensitive runtime management of adaptive applications

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： S. Sinha M. Parashar The Applied Software Systems Laboratory ECE/CAIP Rutgers State University of New Jersey Piscataway NJ USA

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