Lab Publications

Found 132 results
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McDougal, R. A., Hines ML., & Lytton WW. (2013).  Water-tight membranes from neuronal morphology files. J Neurosci Methods. 220, 167–178.
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Newton, A. J. H., McDougal R. A., Hines M. L., & Lytton W. W. (2018).  Using NEURON for reaction-diffusion modeling of extracellular dynamics. Frontiers in Neuroinformatics.
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Neymotin, S.. A., Barczak A.., Oconnell M.. N., Mcginnis T.., Markowitz N.., Espinal E.., et al. (2019).  Tracking rhythmicity of neural oscillations in the auditory thalamocortical system. Society for Neuroscience 2019 (SFN '19).
Neymotin, S.. A., Barczak A.., Oconnell M.. N., Mcginnis T.., Markowitz N.., Espinal E.., et al. (2019).  Tracking rhythmicity of neural oscillations in the auditory thalamocortical system. Society for Neuroscience 2019 (SFN '19).
Lee, GJ., Matsunaga A., Dura-Bernal S., Zhang W., Lytton WW., Francis JT., et al. (2014).  Towards real-time communication between in vivo neurophysiological data sources and simulator-based brain biomimetic models. Journal of Computational Surgery. 3, 12.
Lakatos, P., Barczak A., Neymotin S. A., Lytton WW., Mcginnis T., Javitt D. C., et al. (2014).  Thalamocortical dynamics of rhythmic selective and tonic suppressive modes in the auditory system. Society for Neuroscience 2014 (SFN '14).
Lakatos, P., Barczak A., Neymotin S., Lytton WW., McGinnis T., Javitt D., et al. (2014).  Thalamocortical dynamics of rhythmic selective and tonic suppressive modes in the auditory system. Society for Neuroscience Abstracts. 44,
Erdemir, A., Mulugeta L., & Lytton WW. (2015).  Ten "not so simple" rules for credible practice of modeling & simulation in healthcare. Frontiers in Medical Devices Meeting.
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Tropper, C., Pataory M., Mcdougal R., Hines M., & Lytton WW. (2014).  Stochastic diffusion simulation in NEURON. Society for Neuroscience 2014 (SFN '14).
Choi, J. S., Menzies R. J., Dura-Bernal S., Francis J. T., Lytton WW., & Kerr C. C. (2015).  Spiking network modeling of neuronal dynamics in individual rats. BMC Neuroscience.
C Hunt, A., Erdemir A., Gabhann F. Mac, Lytton WW., Sander E. A., Transtrum M. K., et al. (2018).  The Spectrum of Mechanism-oriented Models for Explanations of Biological Phenomena.
Lytton, WW., Seidenstein AH., Dura-Bernal S., McDougal R. A., Schürmann F., & Hines ML. (2016).  Simulation neurotechnologies for advancing brain research: parallelizing large networks in NEURON. Neural Comput. 28, 2063-2090.
Gleeson, P., Marin B., Sadeh S., Quintana A., Cantarelli M., Dura-Bernal S., et al. (2016).  A set of curated cortical models at multiple scales on Open Source Brain. Computational Neuroscience Meeting (CNS 16').
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McDougal, R. A., Bulanova AS., & Lytton WW. (2016).  Reproducibility in computational neuroscience models and simulations. {IEEE} Trans Biomed Eng. 63, 2021-2035.
McDougal, R., Hines ML., & Lytton WW. (2012).  Reaction-diffusion modeling in the NEURON simulator. Computational Neuroscience.
McDougal, R. A., Skolnick Y., Schaff JC., Lytton WW., & Hines ML. (2012).  Reaction-diffusion modeling in the NEURON simulator. BMC Neuroscience. 13, P119.
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Reaction-Diffusion in the NEURON Simulator. Front Neuroinform. 7:28,
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Uhlrich, DJ., Manning KA., Laughlin ML., & Lytton WW. (2005).  Photic-induced sensitization: acquisition of an augmenting spike-wave response in the adult rat through repeated strobe exposure. Journal of Neurophysiology. 94, 3925-3937.
Seidenstein, A. H., McDougal R. A., Hines M. L., & Lytton WW. (2015).  Parallelizing large networks using NEURON-Python. BMC Neuroscience.
Mcdougal, R. A., Newton A. J. H., Patoary M. N. I., Tropper C., Hines M. L., & Lytton WW. (2017).  Parallel stochastic spines in NEURON reaction-diffusion simulations. Society for Neuroscience 2017 (SFN '17).
Tropper, C., Patoary M. N. I., Mcdougal R. A., Hines M. L., & Lytton WW. (2013).  Parallel stochastic simulation of neuronal reaction-diffusion equations. Society for Neuroscience 2013 (SFN '13).
Patoary, M. Nazrul Ish, Tropper C., McDougal R. A., Lin Z., & Lytton W. W. (2019).  Parallel Stochastic Discrete Event Simulation of Calcium Dynamics in Neuron. IEEE/ACM Trans. Comput. Biol. Bioinform.. 16, 1007–1019.
Patoary, M. Nazrul Ish, Tropper C., McDougal R. A., Zhongwei L., & Lytton WW. (2017).  Parallel Stochastic discrete event simulation of calcium dynamics in neuron.. IEEE/ACM transactions on computational biology and bioinformatics.
Tropper, C., Zhongwei L., Mcdougal R. A., Hines M., & Lytton WW. (2015).  Parallel reaction-diffusion simulation in NEURON. Society for Neuroscience 2015 (SFN '15).
Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.
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Neymotin, SA., Suter BA., Migliore M., Salvador D-B., Shepherd GMG., & Lytton WW. (2015).  Optimizing computer models of layer 5 motor cortex pyramidal neurons using somatic whole-cell recordings. Society for Neuroscience.
Neymotin, S., Suter BA., Dura-Bernal S., Shepherd GM., Migliore M., & Lytton WW. (2017).  Optimizing computer models of corticospinal neurons to replicate in vitro dynamics. J Neurophysiol. 117, 148-162.
Gleeson, P., Cantarelli M., Marin B., Quintana A., Earnshaw M., Piasini E., et al. (2018).  Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits. bioRxiv. 229484.
Mcdougal, R. A., Lytton WW., & Hines M. L. (2011).  Object-oriented reaction-diffusion modeling in the neuron simulator. Society for Neuroscience 2011 (SFN '11).
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Lin, Z., Tropper C., Patoary M. Nazrul Ish, McDougal R. A., Lytton WW., & Hines M. L. (2015).  Ntw-mt: A multi-threaded simulator for reaction diffusion simulations in neuron. Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. 157–167.
Seidenstein, A., Neymotin S. A., Fesharaki A., Hines M. L., Mcdougal R. A., Bulanova A. S., et al. (2015).  Neuronal network bump attractors augmented by calcium up-regulation of Ih in a multiscale computer model of prefrontal cortex. Society for Neuroscience 2015 (SFN '15).
Neymotin, S., McDougal R. A., Sherif MA., Fall CP., Hines ML., & Lytton WW. (2015).  Neuronal calcium wave propagation varies with changes in endoplasmic reticulum parameters: a computer model. Neural Comput. 27, 898–924.
Patoary, M. Nazrul Ish, Tropper C., Lin Z., McDougal R. A., & Lytton WW. (2014).  Neuron time warp. Simulation Conference (WSC), 2014 Winter. 3447–3458.
Mohan, A., Chadderdon G. L., Suter B. A., Shepherd G. M. G., & Lytton WW. (2013).  Network-level coincidence detection in a computer simulation of primary motor cortex. Society for Neuroscience 2013 (SFN '13).
Dura-Bernal, S., Suter B. A., Gleeson P., Cantarelli M., Quintana A., Rodriguez F., et al. (2019).  NetPyNE, a tool for data-driven multiscale modeling of brain circuits. eLife. 8, e44494.
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Lin, Z., Tropper C., McDougal R. A., Patoary M. Nazrul Ish, Lytton WW., Yao Y., et al. (2017).  Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons. ACM Transactions on Modeling and Computer Simulation (TOMACS). 27, 7.
Newton, A., Seidenstein A. H., Hines M. L., Mcdougal R. A., & Lytton WW. (2018).  Multiscale simulation of spreading depolarization in ischemic stroke. Society for Neuroscience 2018 (SFN '18).
Lytton, WW., Arle J., Bobashev G., Ji S., Klassen TL., Marmarelis VZ., et al. (2017).  Multiscale modeling in the clinic: diseases of the brain and nervous system. Brain Inform. 4, 219-230.
Seidenstein, A., Newton A., Macdougal R. A., & Lytton WW. (2017).  Multiscale computer modeling of penumbral zones in brain ischemia. Society for Neuroscience 2017 (SFN '17).
Neymotin, SA., BA S., Migliore M., Salvador D-B., Shepherd GMG., & Lytton WW. (2015).  Motor cortex neurons: from experiment to model via evolutionary algorithms. Computational Neuroscience.
Chadderdon, GL., Mohan A., Suter BA., Neymotin S., Kerr CC., Francis JT., et al. (2014).  Motor cortex microcircuit simulation based on brain activity mapping. Neural Comput. 26, 1239–1262.
Seidenstein, A., Mcdougal R. A., Hines M. L., & Lytton WW. (2016).  Mosaic multiscale computer modeling of ischemic stroke. Society for Neuroscience 2016 (SFN '16).
Taxin, ZH., Neymotin S., Mohan A., Lipton P., & Lytton WW. (2014).  Modeling molecular pathways of neuronal ischemia. Prog Mol Biol Transl Sci. 123, 249–275.
Newton, A., Mcdougal R. A., Hines M. L., Miyazaki K., Ross W. N., & Lytton WW. (2017).  Modeling electrodiffusion with the NEURON reaction-diffusion module. Society for Neuroscience 2017 (SFN '17).
Newton, A., Mcdougal R. A., Hines M. L., Miyazaki K., Ross W. N., & Lytton WW. (2017).  Modeling electrodiffusion with the NEURON reaction-diffusion module. Society for Neuroscience 2017 (SFN '17).
Neymotin, SA., Salvador D-B., Suter BA., Migliore M., Shepherd GMG., & Lytton WW. (2015).  Microconnectomics of primary motor cortex: a multiscale computer model. Multiscale Modeling. National Institutes of Health.
McDougal, RA., Hines ML., & Lytton WW. (2014).  A method for multi-simulator reaction-diffusion with NEURON. Computational Neuroscience.
Womack, KB., Paliotta C., Strain JF., Ho JS., Skolnick Y., Lytton WW., et al. (2017).  Measurement of peripheral vision reaction time identifies white matter disruption in patients with mild traumatic brain injury. J Neurotrauma.
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Lin, Z., Tropper C., Yao Y., McDougal R. A., Patoary MN., Lytton WW., et al. (2017).  Load balancing for multi-threaded PDES of stochastic reaction-diffusion in neurons. J Simulation. 11, 267.
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Kerr, CC., Mo J., Neymotin SA., M D., & Lytton WW. (2011).  Interlaminar Granger causality and alpha oscillations in a model of macaque cortex. Computational Neuroscience.
Kerr, CC., Mo J., Neymotin SA., M D., & Lytton WW. (2011).  Interlaminar Granger causality and alpha oscillations in a model of macaque cortex. Computational Neuroscience.
Kerr, CC., Neymotin SA., Mo J., Schroeder CE., M D., & Lytton WW. (2011).  Interlaminar feedback connections dominate in macaque inferotemporal cortex: in vivo and in silico studies. Society for Neuroscience.
Kerr, CC., Neymotin SA., Mo J., Schroeder CE., M D., & Lytton WW. (2011).  Interlaminar feedback connections dominate in macaque inferotemporal cortex: in vivo and in silico studies. Society for Neuroscience.
Hines, M. L., Mcdougal R., Neymotin S. A., Tropper C., & Lytton WW. (2013).  Interfaces in multiscale reaction-diffusion models in the NEURON simulator. Society for Neuroscience 2013 (SFN '13).
Bulanova, A. S., Mcdougal R. A., Neymotin S. A., Mutai V. K., Lytton WW., & Hines M. L. (2014).  Integrating Systems Biology Markup Language (SBML) with NEURON. Society for Neuroscience 2014 (SFN '14).
Bulanova, A. S., Mcdougal R. A., Neymotin S. A., Mutai V. K., Lytton WW., & Hines M. L. (2014).  Integrating Systems Biology Markup Language (SBML) with NEURON. Society for Neuroscience 2014 (SFN '14).
Bulanova, AS., McDougal RA., Neymotin SA., Mutai V., Lytton WW., & Hines M. (2014).  Integrating Systems Biology Markup Language (SBML) with NEURON. Computational Neuroscience.
Bulanova, AS., McDougal RA., Neymotin SA., Mutai V., Lytton WW., & Hines M. (2014).  Integrating Systems Biology Markup Language (SBML) with NEURON. Computational Neuroscience.
Neymotin, S., Hilscher MM., Moulin TC., Skolnick Y., Lazarewicz MT., & Lytton WW. (2013).  Ih Tunes theta/gamma oscillations and cross-frequency coupling in an in silico CA3 model. PLoS One. 8, e76285.
Hilscher, M. M., Moulin T., Skolnick Y., Lytton W. W., & Neymotin S. A. (2012).  Ih modulates theta rhythm and synchrony in computer model of CA3. Computational Neuroscience Meeting (CNS 12').
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Mcdougal, R. A., Bulanova A. S., Hines M. L., & Lytton WW. (2015).  Hybrid 1d/3d reaction-diffusion in the neuron simulator. Society for Neuroscience 2015 (SFN '15).
Newton, A. J. H., Hines M. L., Lytton W. W., & McDougal R. A. (2019).  Homeostasis and spreading depolarization in multiscale simulation of ischemic stroke.. Society for Neuroscience 2018 (SFN '19).
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Lakatos, P., Barczak A., Neymotin S., McGinnis T., Ross D., Javitt DC., et al. (2016).  Global dynamics of selective attention and its lapses in primary auditory cortex. Nat Neurosci. In press.
Cantarelli, M., Quintana A., Marin B., Earnshaw M., Gleeson P., Court R., et al. (2017).  Geppetto: an open source visualisation and simulation platform for neuroscience. Computational Neuroscience Meeting (CNS 17').
Cantarelli, M., Quintana A., Marin B., Earnshaw M., Gleeson P., Court R., et al. (2017).  Geppetto: an open source visualisation and simulation platform for neuroscience. Computational Neuroscience Meeting (CNS 17').
Cantarelli, M., Marin B., Quintana A., Earnshaw M., Gleeson P., Dura-Bernal S., et al. (2018).  Geppetto: a reusable modular open platform for exploring neuroscience data and models. Phil. Trans. R. Soc. B. 373, 20170380.
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Newton, A. J. H., Seidenstein A. H., McDougal R. A., Hines M., & Lytton W. W. (2018).  Extracellular reaction–diffusion in the NEURON simulator: modeling ischemic stroke. Computational Neuroscience Meeting (CNS 18').
Mcdougal, R. A., Tropper C., Hines M. L., & Lytton WW. (2016).  Expanding NEURON support for reaction-diffusion models. Society for Neuroscience 2016 (SFN '16).
Dura-Bernal, S., Neymotin S., Kerr CC., Sivagnanam S., Majumdar A., Francis JT., et al. (2017).  Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis. IBM Journal of Research and Development. 61, 6–1.
Newton, A.. J. H., Conte C.., Eggleston L.., Blasy E.., Hines M.. L., Lytton W.. W., et al. (2019).  Efficient in silico 3D intracellular neuron simulation. Society for Neuroscience 2019 (SFN '19).
Dura-Bernal, S., Menzies R. J., McLauchlan C., van Albada S. J., Kedziora D. J., Neymotin S., et al. (2016).  Effect of network size on computational capacity. Computational Neuroscience Meeting (CNS 16').
Dura-Bernal, S., Menzies R. J., McLauchlan C., van Albada S. J., Kedziora D. J., Neymotin S., et al. (2016).  Effect of network size on computational capacity. Computational Neuroscience Meeting (CNS 16').
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Dura-Bernal, S., Majumdar A., Neymotin S., Sivagnanam S., Francis J. T., & Lytton WW. (2015).  A dynamic data-driven approach to closed-loop neuroprosthetics based on multiscale biomimetic brain models. IEEE Interanationl Conference on High Performance Computing 2015 Workshop: InfoSymbiotics/Dynamic Data Driven Applications Systems (DDDAS) for Smarter Systems, Bangalore, India.
Dura-Bernal, S., Griffith E. Y., Marczak A., O'Connell N., McGinnis T., Lytton W. W., et al. (2019).  Data-driven model of auditory thalamocortical system rhythms. Society for Neuroscience (SFN '19).
Dura-Bernal, S., Griffith E. Y., Marczak A., O'Connell N., McGinnis T., Lytton W. W., et al. (2019).  Data-driven model of auditory thalamocortical system rhythms. Society for Neuroscience (SFN '19).