How to cite the Neuroscience Gateway

If you used resources available from the NSG for your research, please cite us as follows:
S Sivagnanam, A Majumdar, K Yoshimoto, V Astakhov, A Bandrowski, M. E. Martone, and N. T. Carnevale. Introducing the Neuroscience Gateway, IWSG, volume 993 of CEUR Workshop Proceedings, CEUR-WS.org, 2013.

Neuroscience publications, presentations, posters enabled by NSG:

  1. Chou, Ting-Shuo & J Kashyap, Hirak & Xing, Jinwei & Listopad, Stanislav & Rounds, Emily & Beyeler, Michael & Dutt, Nikil & Krichmar, Jeff. (2018). CARLsim 4: An Open Source Library for Large Scale, Biologically Detailed Spiking Neural Network Simulation using Heterogeneous Clusters. 10.1109/IJCNN.2018.8489326.
  2. R.C. Gerkin, R.J. Jarvis, S.M. Crook, "Toward systematic, data-driven validation of a collaborative, multi-scale model of C. elegans", Philosophical Transactions of the Royal Society B, 373 20170381, 10.1098/rstb.2017.0381, 2018.
  3. J. Birgiolas, R.C. Gerkin, S.M. Crook, "Rapid Selection of NeuroML Models via NeuroML-DB.org", Organization for Computational Neuroscence Meeting, Seattle, 2018.
  4. R.C. Gerkin, R.J. Jarvis, S.M. Crook, "Multiscale Model Validation with SciUnit", Organization for Computational Neuroscience Meeting, Seattle, 2018.
  5. Dura-Bernal S, Neymotin SA, Suter BA, Shepherd GMG, Lytton WW. (2018) Long-range inputs and H-current regulate different modes of operation in a multiscale model of mouse M1 microcircuits. bioRxiv. 201707 [Preprint]; DOI: 10.1101/201707
  6. Gleeson P, Cantarelli M, Quintana A, Earnsah M, Piasini E, Birgiolas J, Cannon RC, Cayco-Gajic A, Crook S, Davison AP, Dura-Bernal S, et al. (2018) Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits. bioRxiv, 229484 [Preprint] (Under review in Neuron)
  7. Cantarelli M, Marin B, Quintana A, Earnshaw M, Court R, Gleeson P, Dura-Bernal S, Silver RA, Idili G (2018). Geppetto: a reusable modular open platform for exploring neuroscience data and models. Phil. Trans. R. Soc. B 20170380. DOI:10.1098/rstb.2017.0380
  8. Dura-Bernal S, Neymotin SA, Suter BA, Shepherd GMG, Lytton WW. (2018) Data-driven multiscale model of primary motor cortex microcircuits. NIH IMAG Multiscale Modeling meeting 2018 (Abstract/Poster)
  9. Dura-Bernal S, Suter BA, Quintana A, Cantarelli M, Gleeson P, Neymotin SA, Hines M, Shepherd GMG, Lytton WW. (2018) NetPyNE: a high-level interface to NEURON to facilitate the development, parallel simulation and analysis of data-driven multiscale network models. Computational Neuroscience (CNS 2018) (Abstract/Poster)
  10. Dura-Bernal S, Suter BA, Quintana A, Cantarelli M, Gleeson P, Rodriguez F, Neymotin SA, Hines M, Shepherd GMG, Lytton WW. (2018) NetPyNE: a GUI-based tool to build, simulate and analyze large-scale, data-driven network models in parallel NEURON. Society for Neuroscience (SFN 2018) (Abstract/Poster)
  11. Latimer B, Bergin DB, Guntu V, Schulz DJ, Nair SS (2018), "Integrating model-based approaches into a neuroscience curriculum An interdisciplinary neuroscience course in engineering," IEEE Transactions on Education (in press).
  12. Astrid A. Prinz, Kun Tian, "An ensemble modeling approach to identifying ion channel correlations," Society for Neuroscience (SfN) Annual Meeting, San Diego, CA, Nov. 3-7, 2018.
  13. Kun Tian, Michael McKinnon, Shawn Hochman, Astrid A. Prinz , "Identifying cellular dynamics in mouse sympathetic neurons: A computational modeling approach", Society for Neuroscience (SfN) Annual Meeting, San Diego, CA, Nov. 3-7, 2018.
  14. Marvin Weigand, "Optimal wiring imposes fixed cortical hypercolumn sizes," Poster, Computational Neuroscience (OCNS) Annual Meeting, Seattle, WA, July 13-18, 2018.
  15. Doherty, DW, Sivagnanam, S., Dura-Bernal, S, and Lytton, WW., "Simulation of avalanches in mouse primary motor cortex (M1)", Poster, Computational Neuroscience (OCNS) Annual Meeting, Seattle, WA, July 13-18, 2018.
  16. Krishnan GP, Rosen BQ, Chen J-Y, Muller L, Sejnowski TJ, Cash SS, et al. (2018) Thalamocortical and intracortical laminar connectivity determines sleep spindle properties. PLoS Comput Biol 14(6): e1006171. https://doi.org/10.1371/journal.pcbi.1006171
  17. Y. Wei, G. P. Krishnan, M. Komarov, M. Bazhenov, "Differential roles of sleep spindles and sleep slow oscillations in memory consolidation", PLos Computational Biology 14(7):e1006322 DOI: 10.1371/journal.pcbi.1006322. July, 2018
  18. Kun Tian, Michael McKinnon, Shaw Hochman, Astrid A. Printz, "An Ensemble Modeling Approach to Identifying Cellular Mechanisms in Thoracic Sympathetic Neurons", Computational Neuroscience (OCNS) Annual Meeting, Seattle, WA, July 13-18, 2018.
  19. N.A. Pelot, B.J. Thio, C.E. Behrend, C.S. Henriquez, W.M. Grill, "Computational Modeling of Neural Stimulation: Electrical Parameter Values and Numerical Methods", Postar, Neural Interfaces Conference, Minneapolis, MN, June, 2018.
  20. E.D. Musselman, N.A. Pelot, G. Goldhagen, W.M. Grill, "Nerve Fiber Recruitment in a Model of Human Cervical Vagus Nerve Stimulation," Poster, Neural Interfaces Conference, Minneapolis, MN, June, 2018.
  21. R.C. Gerkin, R.J. Jarvis, S.M. Crook, "Multiscale Model Validation with SciUnit", Organization for Computational Neuroscience Meeting, Seattle, 2018.
  22. Lealem Mulugeta, Andrew Drach, Ahmet Erdemir, C. A. Hunt, Marc Horner, Joy P. Ku, Jerry G. Myers Jr., Rajanikanth Vadigepalli and William W. Lytton, "Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience", Front. Neuroinform. 12:18. doi: 10.3389/fninf.2018.00018, April, 2018.
  23. Jason S. Sherfey, Austin E. Soplata, Salva Ardid, Erik A. Roberts, David A. Stanley, Bengamin R. Pittman-Polletta, Nancy J. Kopell, "DynaSim: A MATLAB Toolbox for neural Modeling and Simulation, " Frontiers in Neuroinformatics, Vol. 12, March 2018 ,URL=https://www.frontiersin.org/article/10.3389/fninf.2018.00010 DOI=10.3389/fninf.2018.00010
  24. Oliva, Valeria & Cartoni, Emilio & Latagliata, Emanuele & Puglisi-Allegra, Stefano & Baldassarre, Gianluca. (2017). Interplay of prefrontal cortex and amygdala during extinction of drug seeking. Brain Structure and Function. 223. 10.1007/s00429-017-1533-9.
  25. Feng F, Headley D, Chen Z, Latimer B, Amir A, Paré D, Nair SS (2017, "Gamma oscillations in BLA - a computational perspective. Gordon Research Conferences: Amygdala Function in Emotion, Cognition, and Disease," Stonehill College, MA, 2017.
  26. Feng F, Headley D, Chen Z, Latimer B, Amir A, Paré D (2017)." Gamma oscillations in BL - a computational perspective," Society for Neuroscience Poster, Washington, DC. 2017.
  27. Feng F, Chen Z, Latimer B, Nair SS (2017). "Gamma oscillations in BLA - a computational perspective," Workshop on Brain Dynamics and Neurocontrol Engineering. Washington University in St. Louis. 2017.
  28. Latimer B, Feng F, Samarth P, Nair SS (2017). "Central amygdala model integrates intra-amygdalar inputs during fear conditioning," Workshop on Brain Dynamics and Neurocontrol Engineering. Washington University in St. Louis.
  29. Latimer B, Feng F, Samarth P, Pare D, Nair SS (2017). "Central amygdala model integrates intra-amygdalar inputs during fear conditioning," Gordon Research Conferences: Amygdala Function in Emotion, Cognition, and Disease. Stonehill College. 2017.
  30. Latimer B, Feng F, Samarth P, Pare D, Nair SS (2017). "Central amygdala model integrates intra-amygdalar inputs during fear conditioning." Society for Neuroscience. Washington, D.C. 2017.
  31. J. M. Allen, S. M. Elbasiouny, "The effects of model composition design choices on high-fidelity simulations of motoneuron recruitment and firing behaviors", Accepted Manuscript online 28 November 2017, Journal of Neural Engineering , 2017 IOP Publishing Ltd., http://iopscience.iop.org/article/10.1088/1741-2552/aa9db5/meta
  32. D. Caligiore, F. Mannella, M. A. Arbib, G. Baldassarre, "Dysfunctions of the basal ganglia-cerebellar-thalamo-cortical system produce motor tics in Tourette syndrom," PLOS Computational Biology, March 30, 2017, https://doi.org/10.1371/journal.pcbi.1005395
  33. Urszula Fory, Natalia Z. Bielczyk, Katarzyna Piska, Martyna Pomecka, and Jan Poleszczuk,"Impact of Time Delay in Perceptual Decision-Making: Neuronal Population Modeling Approach," Complexity, vol. 2017, Article ID 4391587, 14 pages, 2017. doi:10.1155/2017/4391587.
  34. Piskala, K., Plomecka, M., Bielczyk, N. (2017). Neural mass with short-term synaptic plasticity (STP) as a model of a winner-take-all competition in sensory systems. Proceedings of the XXIV National Conference on Application of Mathematics in Biology and Medicine, Jugowice, September 11th-15th.
  35. Tikidji-Hamburyan Ruben A., Narayana Vikram, Bozkus Zeki, El-Ghazawi Tarek A. "Software for Brain Network Simulations: A Comparative Study ", Frontiers in Neuroinformatics, 11(2017) 46 URL http://journal.frontiersin.org/article/10.3389/fninf.2017.00046, DOI 10.3389/fninf.2017.00046, ISSN1662-5196
  36. Dura-Bernal S, Neymotin S.A., Kerr C.C., Sivagnanam S., Majumdar A., Francis J.T., Lytton W.W., "Evolutionary algorithm optimization of biological parameters in a biomimetic neuroprosthesis," IBM Journal of Research and Development, Vol. 61; Issue 2/3, March-May, 2017.
  37. Allen JM (2017) Effects of abstraction and assumptions on modeling motoneuron pool output. In: Neuroscience, Cell Biology, and Physiology. Dayton, OH: Wright State University.
  38. Mousa MH (2017) Computer modeling of calcium and potassium channels dendritic distributions in spinal motoneurons. In: Systems and Biomedical Engineering. Giza, Egypt: Cairo University.
  39. R.J. Jarvis, S.M. Crook, R.C. Gerkin, "Optimization of Reduced Models against Diverse Experimental Neuron Physiology Datasets with NeuronUnit", CRCNS PI Meeting, Brown University, 2017
  40. Karunamuni R, Seibert TM, White NS, McEvoy L, Farid N, Brewer JB, Dale AM, McDonald CR, and Hattangadi-Gluth JA. 2017. Abnormalities in hippocampal volume of glioma patients prior to radiotherapy. Acta Oncologica. 56(3):427-30
  41. R.J. Jarvis, S.M. Crook, R.C. Gerkin, Parallel Model Optimization against Experimental Neuron Physiology Data with DEAP and NeuronUnit, INCF Meeting, Malaysia, 2017
  42. O. Nolasco-Jáuregui an J. Leyva-Montiel, "Headers and Payloads Inside of Nervous System as Like as Digital Communication Protocols," International Journal of Biomedical Engineering and Science (IJBES), Vol. 4, No. 1, January 2017.
  43. Karunamuni R, Hattangadi-Gluth J. Dose-Dependent Cortical Thinning After Partial Brain Irradiation in High-Grade Glioma. International Journal of Radiation Oncology, Biology, and Physics. 2016 Feb 1;94(2):297-304.
  44. R.C. Gerkin, J.Birgiolas, K. Dai, S.M. Crook, "Data-driven validation of computational neuron models", Collaborative Development of Data-Driven Models of Neural Systems, Janelia Farm, 2016
  45. Karunamuni RA, Hattangadi-Gluth J. Radiation sparing of cerebral cortex in brain tumor patients using quantitative neuroimaging. Radiotherapy and Oncology 2016 Jan;118(1):29-34.
  46. Connor M, Hattangadi-Gluth J. Dose dependent white matter damage after brain radiotherapy. Radiotherapy and Oncology 2016 Nov;121(2):209-216.
  47. Connor M, Hattangadi-Gluth JA. Regional susceptibility to dose dependent white matter damage after brain radiotherapy. Radiotherapy and Oncology. 2017 Apr 28. (in press)
  48. Seibert TM, Hattangadi-Gluth JA. Cerebral Cortex Regions Selectively Vulnerable to Radiation Dose-Dependent Atrophy. International Journal of Radiation Oncology, Biology, and Physics. 2017 Apr 1;97(5):910-918.
  49. Seibert TM, Hattangadi-Gluth JA. Radiation Dose-Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging. International Journal of Radiation Oncology, Biology, and Physics. 2017 Feb 1;97(2):263-269.
  50. Jun J, Mitelut C, Lai C, Gratiy S, Anastassiou C, Harris T., Real-time spike sorting platform for high-density extracellular probes with ground-truth validation and drift correction (bioRxiv; 2017).
  51. Mitelut C., Gratiy SL, Denman D, Siegle JH, Durand S, Godfrey K, Lee C, Reid C, Hawrylycz M, Koch C, Swindale NV, Anastassiou C, Standardizing spike sorting: an in vitro, in silico and In vivo study to develop quantitative metrics for sorting extracellularly recorded spiking activity, (SFN 2015).
  52. Mitelut C., Gratiy SL, Durand S, Mizuseki K, Godfrey K, Lee C, Blanche T, Swindale N, Reid C, Hawrylycz M, Koch C, Anastassiou C, On spike detection and the development of quantitative measures for spike clustering using "ground truth" data: A computational and slice electrophysiology study. (SFN 2014).
  53. Jun J, Steminetz N, Siegle J, Denman D, Bausa M, Barbarits B, Anastassiou C, Andrei A, Aydin C, Barbic M, Blanche T, Bonin V, Carandini M, Couto J, Dutta B, Gratiy S, Gusnisky D, Harris K, Hausser M, Karsh B, Koch C, Ledochowitsch P, Lee A, Mora Lopez C, Mitelut C, Musa S, O'Keefe J, Okun M, Pachiatriu M, Putzeys J, Rich, PD, Rossant C, Sun W, Svoboda K, Harris T et al, "ully integrated silicon probes for high-density recording of neural activity", Nature volume 551, pages 232-236, 2017.
  54. Pelot NA, Behrend C, Grill W. Modeling the response of small myelinated axons in a compound nerve to kilohertz frequency signals, J. Neural Engineering, 2017 Mar 31, doi: 10.1088/1741-2552/aa6a5f
  55. Bielczyk, N., Piskaa, K., Pomecka, M., Todorova, L., Poleszczuk, J., Fory U. (2017). A Switch Between Cooperation and Competition: Hopf Bifurcation as a Mechanism for Decision Making in Presence of Ambivalent Stimuli. Front Comp Neurosci. (under review)
  56. Karunamuni, Roshan A., Tyler M. Seibert, Nathan S. White, Linda McEvoy, Nikdokht Farid, James Brewer, Anders M. Dale, Carrie R. McDonald, and Jona A. Hattangadi-Gluth. "Abnormalities in hippocampal volume of glioma patients prior to radiotherapy." Acta Oncologica (2017): 1-4.
  57. Krishnan, Giri P., Sylvain Chauvette, Isaac Shamie, Sara Soltani, Igor Timofeev, Sydney S. Cash, Eric Halgren, and Maxim Bazhenov. "Cellular and neurochemical basis of sleep stages in the thalamocortical network." eLife 5 (2016): e18607.
  58. Short SM, Morse TM, McTavish TS, Shepherd GM, and Verhagen, "Respiration Gates Sensory Input Resonses in the Mitral Cell Layer of the Olfactory Bulb," PLoS One, 2016 Dec 22; 11(12);e0168356. doi:10.1371/journal.pone.0168356. eCollection 2016.
  59. Marianne J Bezaire, Ivan Raikov, Kelly Burk, Dhrumil Vyas, Ivan Soltesz, "Interneuronal mechanisms of hippocampal theta oscillation in a full-scale model of the rodent CA1 circuit," eLife December 2016; 10.7554/eLife.18566; DOI: http://dx.doi.org/10.7554/eLife.18566.
  60. Samuel A Neymotin, Benjamin A Suter, Salvador Dura-Bernal, Gordon M. G. Shepherd, Michele Migliore, William W. Lytton, "Optimizing computer models of corticospinal neurons to replicatae in vitro dynamics," Journal of Neurophysiology Oct 2016, Vol. 117, pages 148--162, Jn. 00570.2016; DOI: 10.1152/jn.00570.2016
  61. Evans, Benjamin D., and Konstantin Nikolic. "From bytes to insights with modelling as a service a new paradigm for computational modelling illustrated with PyRhO." In Biomedical Circuits and Systems Conference (BioCAS), 2016 IEEE, pp. 316-319. IEEE, 2016.
  62. William W. Lytton, Alexandra H. Seidenstein, Salvador Dura-Bernal, Robert A. McDougal, Felix Schurmann and Michael L. Hines , "Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON," Neural Computation 2016 28:10, 2063-2090 .
  63. G. P. Krishnan, M. Komarov, S. Skorheim, M. Bazhenov, "Slow-wave sleep improves learning through spike sequence replay", Poster, Society for Neuroscience Annual Meeting, San Diego, Nov 12-16, 2016.
  64. P. Sanda, P. Malerba, G. P. Krishnan, M. Bazhenov, "Precise Ripple Timing affects Spatio-Temporal pattern of sleep slow oscillations in a Model of Memory Consolidation", Poster, Society for Neuroscience Annual Meeting, San Diego, Nov 12-16, 2016.
  65. P. Malerba, A. L. Fodder, M. W. Jones, M. Bazhenov, "Modeling of coordinated sequence replay in ca3 and ca1 during sharp wave-ripples", Poster, Society for Neuroscience Annual Meeting, San Diego, Nov 12-16, 2016.
  66. Y. Wei, G. P. Krishnan, M. Bazhenov, "Effect of learning cues on sleep-related memory consolidation depends on the phase of sleep slow oscillation," Poster, Society for Neuroscience Annual Meeting, San Diego, Nov 12-16, 2016.
  67. Y. Wei, G. P. Krishnan, M. Bazhenov, "Synaptic mechanisms of memory consolidation during NREM sleep", Poster, Society for Neuroscience Annual Meeting, San Diego, Nov 12-16, 2016.
  68. Short SM, Morse TM, McTavish TS, Shepherd GM, Verhagen JV, "Respiration Gates Sensory Input Responses in the Mitral Cell Layer of the Olfactory Bulb," poster 524. 38th Annual AChemS Meeting, 2016.
  69. McDougal, Robert A. and Morse, Thomas M. and Carnevale, Ted and Marenco, Luis and Wang, Rixin and Migliore, Michele and Miller, Perry L. and Shepherd, Gordon M. and Hines, Michael L., "Twenty years of ModelDB and beyond: building essential modeling tools for the future of neuroscience", journal="Journal of Computational Neuroscience", year="2016", pages="1--10",issn="1573-6873", doi="10.1007/s10827-016-0623-7", url="http://dx.doi.org/10.1007/s10827-016-0623-7"
  70. Rumbell, Timothy H., Danel Dragulji., Aniruddha Yadav, Patrick R. Hof, Jennifer I. Luebke, and Christina M. Weaver. "Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons." Journal of computational neuroscience (2016): 1-26. http://www.ncbi.nlm.nih.gov/pubmed/27106692
  71. Van Geit W, Gevaert M, Chindemi G, Rossert C, Courcol J, Muller EB, Schurmann F, Segev I and Markram H (2016). BluePyOpt: Leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience. Front. Neuroinform. 10:17. doi: 10.3389/fninf.2016.00017
  72. R. McDougal; A. Bulanova; W. Lytton, "Reproducibility in Computational Neuroscience Models and Simulations," in IEEE Transactions on Biomedical Engineering , vol. 63, pages. 2021--2035, doi: 10.1109/TBME.2016.2539602
  73. Hodge, Victoria; Jessop, Mark; Fletcher, Martyn; Weeks, Michael; Turner, Aaron; Jackson, Tom; Ingram, Colin; Smith, Leslie and Austin, Jim", "A Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience", journal="Neuroinformatics", vol. 14, no. 1, pp 23-40, year 2016.
  74. Dura-Bernal S, Suter BA, Neymotin SA, Kerr CC, Quintana A, Gleeson P, Shepherd GMG, Lytton WW. NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks. Computational Neuroscience (CNS), 2016.
  75. Guet-McCreight A, Camire. O, Topolnik L, Skinner FK. Using A Semi-Automated Strategy To Develop Multi-Compartment Models That Predict Biophysical Properties Of Interneuron Specific 3 (IS3) Cells In Hippocampus. eNeuro. 3(4). 2016, pii: ENEURO.00877-16.2016 .
  76. Short SM, McTavish TS, Morse TM, Shepherd GM, Verhagen JV," Circuit models identify mechanisms of respiration driven lateral inhibition underlying mitral activity", SfN Nanosymposium 561.08, 2015.
  77. Shahand, S. (2015). Science gateways for biomedical big data analysis.
  78. Dura-Bernal S, Majumdar A, Neymotin SA, Sivagnanam S, Francis JT, Lytton WW. A dynamic data-driven approach to closed-loop neuroprosthetics based on multiscale biomimetic brain models. IEEE Conference on High Performance Computing 2015 Workshop: Dynamic Data Driven Applications Systems (DDDAS), 2015.
  79. Stockton DB, Santamaria F. NeuroManager: a workflow analysis based simulation management engine for computational neuroscience. Frontiers in Neuroinformatics. 2015;9:24. doi:10.3389/fninf.2015.00024.
  80. S.A Neymotin, B.A. Suter, M. Migliore, S. Dura-Bernal, G.M.G. Shepard, W.W. Lytton, .Optimizing computer models of layer 5 motor cortex pyramidal neurons using somatic whole cell recordings,. Society for Neuroscience Annual Meeting (poster), Chicago, IL, October, 2015.
  81. Dura-Bernal S, Suter BA, Neymotin SA, Quintana AJ, Gleeson P, Shepherd GMG, Lytton WW. .Normalized cortical depth (NCD) as a primary coordinate system for cell connectivity in cortex: experiment and model.. Society for Neuroscience (SFN), Chicago, IL, October 2015.
  82. A. Seidenstein, S.A. Neymotin, A. Fesharaki, M.L. Hines, R.A., McDougal, A.S. Bulanova, W.W. Lytton, .Neuronal network bump attractors augmented by calcium up-regulation of lh in multiscale computer model of prefrontal cortex,. Society for Neuroscience Annual Meeting (poster), Chicago, IL, October, 2015.
  83. C. Mitelut, S. L. Gratiy, D. Denman, J. H. Siegle, S. Durand, K. Godfrey, C. Lee, R.C. Reid, M. Hawrylycz, C. Koch, N.V. Swindle, C. Anastassiou, .Standardizing spike sorting: an In vitro, in silico and In vivo study to develop quantitative metrics for sorting extracellularly recorded spiking activity,. Society for Neuroscience Annual Meeting (poster), Chicago, IL, October, 2015.
  84. A.H. Seidenstein, R.A. McDougal, M.L. Hines, A.Fesharaki, W.W. Lytton, .Parallelizing large networks using NEURON-python,. Computational Neuroscience (CNS) Annual Meeting (poster), Prague, July, 2015.
  85. Pelot, Nicole A., Christina E. Behrend, and Warren M. Grill. "Modeling the response of small myelinated and unmyelinated axons to kilohertz frequency signals." In 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 406-409. IEEE, 2015.
  86. Shahand, Shayan, Ammar Benabdelkader, Mohammad Mahdi Jaghoori, Mostapha al Mourabit, Jordi Huguet, Matthan WA Caan, Antoine HC Kampen, and Sílvia D. Olabarriaga. "A data‐centric neuroscience gateway: design, implementation, and experiences." Concurrency and Computation: Practice and Experience 27, no. 2 (2015): 489-506.
  87. Neymotin SA, Suter BA, Migliore M, Dura-Bernal S, Shepherd GMG, Lytton WW. Optimizing computer models of layer 5 motor cortex pyramidal neurons using somatic whole-cell recordings. Society for Neuroscience (SFN), 2015.
  88. M. Schirner, S. Rothmeier, V. K. Jirsa, A. R. McIntosh, P. Ritter, An Automated Pipeline for Constructing Personalized Virtual Brains from Multimodal Neuroimaging Data, NeuroImage, March 2015; doi:10.1016/j.neuroimage.2015.03.055
  89. Rumbell, Timothy, Danel Dragulj., Jennifer Luebke, Patrick Hof, and Christina M. Weaver. "Prediction of ion channel parameter differences between groups of young and aged pyramidal neurons using multi-stage compartmental model optimization." BMC Neuroscience 16, no. 1 (2015): 1.
  90. Forrest MD, .Simulation of Alcohol Action upon a Detailed Purkinje Neuron Model and a Simpler Surrogate Model that runs >400 times faster.. BMC Neuroscience 2015, 16:27.
  91. Guet-McCreight A, Camire. O, Topolnik L, Skinner FK. (2016). Poster Presentation: Developing Multi-Compartment Models of Interneuron Specific 3 (IS3) Cells in Hippocampus Using a Semi-Automated Approach. 2-B-17 CAN2016, Canadian Association for Neuroscience, May, 2016.
  92. T. Rumbell, D. Draguljic, J. I. Luebke, P. R. Hof, C. M. Weaver, .Compartmental model optimization predicts altered channel densities and kinetics in aged versus young pyramidal neurons of rhesus monkey prefrontal cortex., Society for Neuroscience Annual Meeting, Washington D.C., Nov. 15-19, 2014.
  93. Rumbell, Timothy, Danel Dragulji., Jennifer Luebke, Patrick Hof, and Christina M. Weaver., "Automatic fitness function selection for compartment model optimization." BMC Neuroscience 15, no. Suppl 1 (2014): O5.
  94. Lee S, Marchionni I, Bezaire MJ, Danielson N, Lovett-Barron M, Losonczy A, Soltesz I. (2014) .GABAergic Basket Cells Differentiate Among Hippocampal Pyramidal Cells. Neuron., 1129-1144, June 4, 2014.
  95. Ingber L, Pappalepore M, and Stesiak R, .Electroencephalographic fiend influence on calcium momentum waves,. Journal of Theoretical Biology, Volume 343, pp 138-153, February 2014.

Cyberinfrastructure related NSG publications, presentationa, posters:

  1. N.T. Carnevale, S. Sivagnanam, K. Yoshimoto, A. Majumdar, "The Neuroscience Gateway: enabling large scale modeling and data processing in neuroscience", Poster Society for Neuroscience (SfN) Annual Meeting, San Diego, CA, Nov 3-7, 2018.
  2. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale, A. Peyser, "High Performance Computing Resources for Parallel Simulations and Data Analysis: NSG and HPAC," NSG Satellite Workshop at Society for Neuroscience (SfN) Annual Meeting, San Diego, CA, Nov 3-7, 2018.
  3. K. Yoshimoto, "Neuroscience Gateway - Scalable infrastructure for computationally-intensive cognitive neuroscience", Tutorial at CogSci18, Wisconsin, MD, July 25-28, 2018.
  4. S. Sivagnanam, K. Yoshimoto, T. Carnevale, A. Majumdar, "The Neuroscience Gateway - Enabling Large Scale Modeling and Data Processing in Neuroscience," Practice & Experience in Advanced Research Computing PEARC18, Pittsburgh, PA, July 22-26, 2018.
  5. M. Pierce, M. Miller, A. Majumdar, S. Pamidighantam, S. Marru, "Introduction to Science Gateways for New Users," Tutorial, Practice & Experience in Advanced Research Computing PEARC18, Pittsburgh, July 22-26, 2018.
  6. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale, "Neuroscience Gateway and Large Scale Neural Systems Simulations and Tools," Workshop, Organization of Computational Neuroscience (CNS) Annual Conference, Seattle, WA, July 13-18, 2018.
  7. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale, "Neuroscience Gateway - Enabling Large Scale Simulations and Data Processing and Dissemination of Neuroscience Tools/Software", Poster, Organization of Computational Neuroscience (CNS) Annual Conference, Seattle, WA, July 13-18, 2018.
  8. S. Sivagnanam, "Enabling computational modeling and big data analysis through Neuroscience Gateway," Neural Interfaces Conference, Minneapolis June 2018.
  9. S. Sivagnanam, A. Majumdar, K. Yoshimoto, T. Carnevale, "Neuroscience Gateway: Enabling Easy Path to Supercomputing for Neuroscience Research and Education," Poster, Neural Interfaces Conference 2018, Minneapolis, MN, June 25-27, 2018.
  10. A. Wagner, K Pezzoli, A. Majumdar, J. Bottum, N. Wilkins-Diehr, "Science Gateways and their impact on research and scholarship nationally and internationally," Internet 2, Global Summit, May 6-9, 2018, San Diego, CA.
  11. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale, "Neuroscience gateway - enabling easy path to supercomputing for neuroscience research and education," BRAIN Initiative PI Meeting, Bethesda, MD, April 9-14, 2018.
  12. A. Majumdar, S. Sivagnanam, K. Yoshimoto (UCSD), N.T. Carnevale (Yale U.), A. Peyser (Jülich Supercomputer Center), "High Performance Computing (HPC) Resources for Parallel Simulations and Data Analysis: NSG and HPAC," Satellite Workshop, Society for Neuroscience Annual Meeting 2017, Washington D.C., November 2017.
  13. T. Carnevale, A. Majumdar, S. Sivagnanam, K. Yoshomoto, "The Neuroscience Gateway Portal: high performance computing for neuroscientists", Poster, Society for Neuroscience Annual Meeting, Nov 10-15, 2017, Washington D.C.
  14. A. Majumdar, "Neuroscience Gateway," August, 2017, NEUROCOMP17, Madison, WI.
  15. A. Majumdar, S. Sivagnanam, T. Carnevale, "Neuroscience Gateway: Enabling Developers and Users to Utilize Open High Performance Computing Resources for Large Scale Simulations," Workshop Computational Neuroscience Annual Meeting (CNS 2017), July 2017, Antwerp, Belgium.
  16. T. Carnevale, A. Majumdar, S. Sivagnanam, K. Yoshimoto, "The Neuroscience Gateway Portal - High Performance Computing for Neuroscientists," Computational Neuroscience Annual Meeting (CNS 2017) Poster Presentation, Antwerp, Belgium, July 2017.
  17. A. Majumdar, "Science Gateways - Access to HPC", University of California Los Angeles, April, 2017.
  18. A. Majumdar, "HPC Resources and Science Gateways,", University of California Davis, March, 2017.
  19. Supun Nakandala, Suresh Marru, Marlon Pierce, Sudhakar Pamidighantam, Kenneth Yoshimoto, Terri Schwartz, Subhashini Sivagnanam, Amit Majumdar and Mark Miller, "Apache Airavata Sharing Service: A Tool for Enabling User Collaboration in Science Gateways," PEARC17, July 09-13, 2017, new Orleans, LA, USA. ACM ISBN 978-1-4503-5272-7/17/07.
  20. S. Strande, H. Cai, T. Cooper, K. Flammer, C. Irving, G. Laszewski, A. Majumdar, D. Mishin, P. Papadopoulos, W. Pfeiffer, R. Sinkovits, M. Tatineni, R. Wagner, F. Wang, N. Wilkins-Diehr, N. Wolter, and M. Norman, "Comet - Tales from the Long Tail - Two Years In and 10,000 Users Later," PEARC17, July 09-13, 2017, new Orleans, LA, USA. ACM ISBN 978-1-4503-5272-7/17/07. http://dx.doi.org/10.1145/3093338.3093383
  21. A. Majumdar, S. Sivagnanam, T. Carnevale, K. Yoshimoto, "The Neuroscience Gateway - Enabling Large-Scale Neuroscience Simulations and Data Processing Using Supercomputers, " Poster, Third Annual BREAIN Initiative PI Meeting, Bethesda, MD, Dec 12-14, 2016.
  22. S. Sivagnanam, A. Majumdar, P. Kumbhar, M. Hines, K. Yoshomoto, T. Carnevale, "Neuroscience Gateway - Understanding the scaling behavior of NEURON application, " Poster, SC16, Salt Lake City, Utah, November, 2016.
  23. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnecvale, "Understanding Collaborative Cyberinfrastructure Need of Neuroscientists - Survey Results", White Paper, September, 2016.
  24. S. Sivagnanam, A. Majumdar, K. Yoshimoto, T. Carnevale, "NSG-R: Programmatic Access to Neuroscience Applications on HPC," Poster XSEDE16, Miami, July 17-21, 2016.
  25. N. T. Carnevale, P. Gleeson, R. A. Silver, A. Majumdar, S. Sivagnanam, K. Yoshimoto, "Seamless Integration of Neuroscience Models and Tools with High Performance Computing, " Poster, Society for Neuroscience Annual Meeting, San Diego, Nov 12-16, 2016.
  26. Majumdar, A., Sivagnanam, S., Yoshimoto, K., Carnevale, N. T., Quintana, A., Gleeson, P. and Silver, R. A., "NSG-R Programmatic access to neuroscience applications", poster, Workshop Collaborative Development of Data-Driven Models of Neural Systems, HHMI Janelia Research Campus, Virginia, USA, Sept 18-21, 2016.
  27. Majumdar A, Sivagnanam S, Carnevale NT, Yoshimoto K, Gleeson P, Quintana A and Silver RA (2016), "Neuroscience Gateway - Cyberinfrastructure Providing Supercomputing Resources for Large Scale Computational Neuroscience Research," Front. Neuroinform. Conference Abstract: Neuroinformatics 2016. Neuroinformatics 2016, Reading, United Kingdom, 3 Sep - 4 Sep, 2016. doi: 10.3389/conf.fninf.2016.20.00008
  28. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale, "Understanding the Evolving Cyberinfrastructure Needs of the Neuroscience Community," Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale (XSEDE16). ACM, New York, NY, USA, , Article 45 , 7 pages. DOI: http://dx.doi.org/10.1145/2949550.2949657
  29. S. Sivagnanam, A. Majumdar, K. Yoshimoto, T. Carnevale, "NSG-R: Programmatic Access to Neuroscience Applications," (poster) Proceedings XSEDE16, Miami, July 17-21, 2016.
  30. S. Dura-Bernal, S. A. Neymotin, W. L. Lytton, A. Majumdar, and S. Sivagnanam, " A Dynamic Data-Driven Approach to Closed-loop Neuroprosthetics Based on Multiscale Biomimetic Brain Models," Dynamic data Driven Application Systems Workshop, IEEE International Conference on High Performance Computing, Dec. 16-19, 2015, Bengaluru, India.
  31. S. Sivagnanam, A. Majumdar, P. Kumbhar, M. Hines, K. Yoshimoto, T. Carnevale, .Neuroscience Gateway . Enabling HPC for Computational Neuroscience,. Supercomputing 2015 (poster), Austin, TX, November, 2015.
  32. T. Carnevale, A. Majumdar, S. Sivagnanam, K. Yoshimoto, P. Gleeson, R.A. Silver. Seamless integration of neuroscience models and tools with high performance computing. Poster, Society for Neuroscience Annual Meeting, Chicago, IL, Oct. 17 - 21, 2015.
  33. B. Lytton, M. Hines, .NEURON and the Neuroscience Gateway Portal,. HPC Workshop, 2015 Computational Neuroscience Annual Meeting, Prague, July, 2015.
  34. M. Miller, T. Schwartz, P. Hoover, K. Yoshimoto, S. Sivagnanam, A. Majumdar, "The CIPRES Workbench: A Flexible Framework for Creating Science Gateways", Proceedings XSEDE15, St. Louis, MO, July 26-30, 2015.
  35. 7. A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale, .Neuroscience Gateway . Seamless Access to XSEDE High Performance Computing Resources for the Computational Neuroscience Community,. XSEDE 15 Conference (poster), St. Louis, MO, July 26-30, 2015.
  36. Ted Carnevale, Amit Majumdar, Subhashini Sivagnanam, Kenneth Yoshimoto, Vadim Astakhov, Anita Bandrowski, Maryann Martone, “The Neuroscience Gateway Portal - High Performance Computing Made Easy,” Poster, Computational Neuroscience (CNS) 2014 Annual Meeting, Quebec City, Canada, July 26-31, 2014.
  37. S. Sivagnanam, A. Majumdar, K. Yoshimoto, V. Astakhov, A. Bandrowski, M. Martone, and N. T. Carnevale, "Early experiences in developing and managing the neuroscience gateway," Journal of Concurrency and Computation: Practice and Experience,Vol 27, Issue 2, pages 473-488, 2015 UR: http://dx.doi.org/10.1002/cpe.3283.
  38. Ted Carnevale, Amit Majumdar, Subhashini Sivagnanam, Kenneth Yoshimoto, Vadim Astakhov, Anita Bandrowski, Maryann Martone, " High performance computing in neuroscience via the Neuroscience Gateway Portal", Poster, Society for Neuroscience Annual Meeting, Washington D.C, Nov. 15 - 19, 2014.
  39. Ted Carnevale, Amit Majumdar, Subhashini Sivagnanam, Kenneth Yoshimoto, Vadim Astakhov, Anita Bandrowski, Maryann Martone, .The Neuroscience Gateway Portal - High Performance Computing Made Easy,. BMC Neuroscience, Vol 15, No 1, 2014, doi="10.1186/1471-2202-15-S1-P101", url="http://dx.doi.org/10.1186/1471-2202-15-S1-P101.
  40. N.T. Carnevale, A. Majumdar, S. Sivagnanam, K. Yoshimoto, V. Astakhov, A. Bandrowski, M. Martone, "The Neuroscience Gateway Portal: facilitating access to high performance computing resources," Poster, Society for Neuroscience Annual Meeting, San Diego, Nov. 9-13, 2013.
  41. S. Sivagnanam, K. Yoshimoto, A. Majumdar, N. T. Carnevale, V. Astakhov, M. Martone, A. Bandrowski, "A Neuroscience Gateway: Software and Implementation," Proceedings XSEDE13 Gateway to Discovery, San Diego, CA, July 22-25, 2013.
  42. S. Sivagnanam, A. Majumdar, K. Yoshimoto, N. T. Carnevale, V. Astakhov, A. Bandrowski, M. Martone, "Introducing The Neuroscience Gateway," Proceedings International Workshop on Science Gateways , Zurich, Switzerland, June 3-5, 2013.
  43. N.T. Carnevale, S. Sivagnanam, K. K. Yoshimoto, V. Astakhov, A. E. Bandrowski, M. E. Martone, A. Majumdar, "A Neuroscience Gateway for High Performance Computing," Poster,Society for Neuroscience Annual Meeting, New Orleans, October 13-17, 2012.

Educational projects/publications:

  1. Dura-Bernal S, McDougal R, Lytton WW. (2018) Multiscale modeling from molecular level to large network level (using NEURON, RxD and NetPyNE). Computational Neuroscience (CNS 2018) (Tutorial) - http://www.cnsorg.org/cns-2018-tutorials#T2
  2. Dura-Bernal, S. Development of large scale data-driven network models in NetPyNE, a high-level interface to NEURON. Computation Neuroscience (CNS 2018) Workshop on "Developing, standardizing and sharing large scale cortical network models" (Workshop talk)
  3. VII Latin American School on Computational Neuroscience (LASCON) (2018) Institute of Mathematics and Statistics, University of Sao Paulo, Brazil (Course)
  4. NSG was used during the Human Brain Project School on the Brain Simulation Platform, Palermo 17-21 Sep. 2018. https://www.humanbrainproject.eu/en/follow-hbp/events/the-brain-simulation-platform-hbp-school/
  5. NSG was used by the students attending the Computational Neuroscience Training at the University of Missouri, June, 2018.
  6. NSG was used as a part of a EU HBP workshop titled, "Neuroscience for ICT: Applications to Computation and Robotics", in KALKSCHEUNE BERLIN, GERMANY, July 4-6, 2018. https://education.humanbrainproject.eu/web/2nd-hbp-curriculum-workshop-series/ict-workshop
  7. NSG was used by the students of the course " Neuroscience Simulation" taught by EPFL researchers, May, 2018
  8. Neuroscience Information Framework (NIF) organized webinar on the Neuroscience Gateway Project, Subhashini Sivagnanam, September 29, 2017.
  9. NSG webinar tutorial was given for the NIH BRAIN Initiative Summer Course on Models and Neurobiology. at University of Missouri, Columbia, MO, June 13, 2016. 24 pre- and post-docs and faculties attended this workshop which was funded by NIH R25 Research and Training grant http://engineering.missouri.edu/neuro/outreach/nih-neuroscience-course/
  10. Dervinis, Martynas 2016. Pathophysiological mechanisms of absence epilepsy: a computational modelling study. PhD Thesis, Cardiff University
  11. S. Sahand, .Science Gateways for biomedical big data analysis,. Ph. D Thesis, 2015, University of Amsterdam, http://hdl.handle.net/11245/1.490613
  12. Alexandre Guet McCreight, .Predicting Cell-Type Specific Active Properties by Developing Multi-Compartment Models Using Databases and Electrophysiological Feature Constraints: Application to Interneuron Specific 3 (IS3) Cells in the Hippocampus., Master.s Thesis, University of Toronto, August, 2015.
  13. Kait Folweiler, .Computational Model of the Dentate Gyrus,. Ph.D qualifying research, 2015, University of Pennsylvania.
  14. Another research project, titled, .Dendritic Excitation Dependence on Synaptic Democracy in CA1 Pyramidal Neurons,. Chung, P, George, V, and Hermiz, J used the NSG for their research. Ref. http://www.isn.ucsd.edu/courses/bggn260/2013/reports/Chung_George_Hermiz.pdf (2014)
  15. NSG was used in a class project by graduate student Nikki Pelot, Biomedical Engineering, Duke University, 2014.
  16. The NSG was used by attendees of the Open Source Brain Hackathon in London in November, 2013 (http://www.opensourcebrain.org/projects/osb/wiki/Hackathon2013), where users tested large scale models of cortical networks on the NSG provided resources during the meeting. This was reported by Padraig Gleeson who ran the workshop and is from the Department of Neuroscience, Physiology and Pharmacology, University College of London.