Lab Publications | Neurosim lab

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Lytton, WW. (2006). Neural query system: data-mining from within the NEURON simulator. Neuroinformatics. 4, 163-176.

Kerr, CC., O'Shea DJ., Goo W., Dura-Bernal S., Francis JT., Diester I., et al. (2014). Network-level effects of optogenetic stimulation in a computer model of macaque primary motor cortex. BMC Neuroscience. 15, P107.

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., BA S., Kerr C. C., Quintana A., Gleeson P., Shepherd GMG., et al. (2016). NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks. Computational Neuroscience.

Dura-Bernal, S., Suter B. A., Quintana A., Cantarelli M., Gleeson P., Rodriguez F., et al. (2018). NetPyNE: A GUI-based tool to build, simulate and analyze large-scale, data-driven network models in parallel NEURON. Society for Neuroscience 2018 (SFN '18).

Lytton, WW., Neymotin S., Wester JC., & Contreras D. (2014). Neocortical simulation for epilepsy surgery guidance: localization and intervention. (Bass, B., & Garbey M., Ed.).Computational Surgery and Dual Training. 339–349.

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Zhu, JJ., Uhlrich D., & Lytton WW. (1996). Muscarinic receptor mediated responses in thalamic local interneurons. snabs. 22, 574.8.

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.

Neymotin, S., Dura-Bernal S., Lakatos P., Sanger TD., & Lytton WW. (2016). Multitarget multiscale simulation for pharmacological treatment of dystonia in motor cortex. Front Pharmacol. 7, 157.

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. (2018). Multiscale modeling of brain disease. 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.

Lytton, WW., Neymotin S., & Kerr CC. (2014). Multiscale modeling for clinical translation in neuropsychiatric disease. J Comput Surgery. 1, 7.

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).

Lytton, WW., Vadigepalli R., & Kramer MA. (2015). Multiscale Computational Modeling for the US BRAIN initiative.

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).

Dura-Bernal, S., Li K., Brockmeier A., Kerr C., Neymotin S., Principe J., et al. (2014). Modulation of virtual arm trajectories via microstimulation in a spiking model of sensorimotor cortex. BMC Neuroscience. 15, P106.

Kerr, CC., Neymotin SA., Song W., Francis JT., & Lytton WW. (2011). Modulation of stimulus fields in a computer model of the thalamocortical system. Society for Neuroscience.

Lytton, WW., & Thomas E. (1999). Modeling thalamocortical oscillations. (Ulinski, P., Jones EG., & Peters A., Ed.).Cerebral Cortex. 13, 479-509.

Knox, A. T., Glauser T., Tenney J., Lytton WW., & Holland K. (2018). Modeling pathogenesis and treatment response in childhood absence epilepsy. Epilepsia. 59, 135–145.

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).

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.

Neymotin, S., Lytton WW., Olypher AO., & AA F. (2011). Measuring the quality of neuronal identification in ensemble recordings. jnsci. 31, 16398–16409.

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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Dura-Bernal, S., Neymotin S., 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.

Dura-Bernal, S., Neymotin S. A., Suter B. A., Shepherd G. M., & Lytton WW. (2017). Long-range inputs and H-current regulate different modes of operation in a multiscale model of mouse M1 microcircuits. Society for Neuroscience 2017 (SFN '17).

Lytton, WW., & Kristan WB. (1989). Localization of a leech inhibitory synapse by photo-ablation of individual dendrites. 504, 43-48.

Orman, R., Von Gizycki G., Lytton WW., & Stewart M. (2008). Local axon collaterals of area ca1 support spread of epileptiform discharges within CA1, but propagation is unidirectional. Hippocampus. 18, 1021-1033.

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.

Dura-Bernal, S., Kerr C., Neymotin S., Suter B., Shepherd G., Francis J., et al. (2015). Large-scale M1 microcircuit model with plastic input connections from biological PMd neurons used for prosthetic arm control. 24th Annual Computational Neuroscience Meeting (CNS15).

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Neymotin, S., Lazarewicz MT., Sherif M., Contreras D., Finkel LH., & Lytton WW. (2011). Ketamine disrupts theta modulation of gamma in a computer model of hippocampus. J Neurosci. 31, 11733-11743.

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Lytton, WW., Omurtag A., Neymotin S., & Hines ML. (2008). Just-in-time connectivity for large spiking networks. ncomp. 20, 2745-2756.

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Zhu, JJ., Lytton WW., Xue JT., & Uhlrich D. (1999). An intrinsic oscillation in interneurons of the rat lateral geniculate nucleus. jnphys. 81, 702-711.

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.

Neymotin, S., Lee HY., Fenton AA., & Lytton WW. (2010). Interictal EEG Discoordination in a Rat Seizure Model. J Clin Neurophysiol. 27, 438–444.

Neymotin, SA., H L., AA F., & Lytton WW. (2010). Interictal EEG discoordination in a rat seizure model. Statistical Analysis of Neuronal Data.

Dura-Bernal, S., Zhou X., Chadderdon G. L., Przekwas A., & Lytton WW. (2013). Interfacing a biomimetic model of sensorimotor cortex with a musculoskeletal model and a robotic arm. Society for Neuroscience 2013 (SFN '13).

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, AS., McDougal RA., Neymotin SA., Mutai V., Lytton WW., & Hines M. (2014). Integrating Systems Biology Markup Language (SBML) with NEURON. Computational Neuroscience.

Olypher, AV., Lytton WW., & Prinz AA. (2012). Input-to-output transformation in a model of the rat hippocampal CA1 network. Front Comput Neurosci. 6, 57.

Deyo, S., & Lytton WW. (1997). Inhibition Can Disrupt Hypersynchrony In Model Neuronal Networks. Progress in neuro-psychopharmacology & biological psychiatry.

Neymotin, S. A., Jacobs K. M., & Lytton WW. (2009). Information transmission vs processing in computer models of neocortical columns. Society for Neuroscience 2009 (SFN '09).

Kerr, C. C., O'Shea D. J., Goo W., Dura-Bernal S., Diester I., Kalanithi P., et al. (2014). Information flow in optogenetically stimulated macaque motor cortex: simulation and experiment. Neural Control of Movement (NCM) meeting.

Lytton, WW., & Hines M. (2005). Independent variable timestep integration of individual neurons for network simulations. 17, 903-921.

Briska, AM., Uhlrich DJ., & Lytton WW. (2000). Independent dendritic domains in the thalamic circuit. Neurocomputing. 32, 299–305.

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.

Doherty, D. W., Dura-Bernal S., Neymotin S. A., & Lytton WW. (2018). Identifying avalanches in simulated mouse primary motor cortex (M1). Society for Neuroscience 2018 (SFN '18).

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Lytton, WW., & Hines M. (2004). Hybrid neural networks - combining abstract and realistic neural units. IEEE Engineering in Medicine and Biology Society Proceedings. 6, 3996-3998.

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).

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Kubie, J. L., Fenton A. A., Lytton WW., & Burgess N. (2009). Grid-cell models for navigation and context discrimination. Society for Neuroscience 2009 (SFN '09).

Neymotin, S., Sherif M. A., Jung J. Q., Kabariti J. J., & Lytton WW. (2018). Genome-wide associations of schizophrenia studied with computer simulation. (Cutsuridis, V., Graham BP., Cobb S., & Vida I., Ed.).Hippocampal Microcircuits: A Computational Modeler's Resource Book. 2,

Kapur, A., Pearce R., Lytton WW., & L H. (1997). \gabaa-mediated IPSCs in piriform cortex have fast and slow components with different properties and locations on pyramidal cells: Study with physiological and modeling methods. jnphys. 78, 2531-2545.

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Lytton, WW. (2002). From Computer to Brain.

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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.

Dura-Bernal, S., Prins N., Neymotin S., Prasad A., Sanchez J., Francis JT., et al. (2014). Evaluating Hebbian reinforcement learning BMI using an in silico brain model and a virtual musculoskeletal arm.. Neural Control of Movement.

Neymotin, SA., H L., Park EH., AA F., & Lytton WW. (2010). Emergent oscillations in neocortex: a simulation study. Dynamical Neuroscience XVIII: The Resting Brain: Not at Rest! Satellite meeting for Society for Neuroscience Meeting.

Neymotin, S., Lee HY., Park EH., Fenton AA., & Lytton WW. (2011). Emergence of physiological oscillation frequencies in a computer model of neocortex. Front Comput Neurosci. 5, 19.

Antic, S. D., Hines M., & Lytton WW. (2018). Embedded ensemble encoding hypothesis: The role of the ``Prepared'' cell. J. Neurosci. Res..

Graham, J. W., Angulo S., Gao P. P., Dura-Bernal S., Sivagnanam S., Hines M.., et al. (2018). Embedded ensemble encoding: A hypothesis for reconciling cortical coding strategies. Society for Neuroscience 2018 (SFN '18).

Rowan, MS., Neymotin S., & Lytton WW. (2014). Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Front Comput Neurosci. 8, 39.

Kerr, CC., Neymotin S., Chadderdon GL., Fietkiewicz CT., Francis JT., & Lytton WW. (2012). Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex. IEEE Trans Neural Syst Rehab Eng. 20, 153–60.

Kerr, CC., van Albada SJ., Chadderdon GL., Neymotin SA., Robinson PA., & Lytton WW. (2012). Effects of basal ganglia on cortical computation: a hybrid network/neural field model. Society for Neuroscience.

Kerr, C., Van Albada S. J., Neymotin S. A., Chadderdon G. L., Robinson P. A., & Lytton WW. (2012). Effects of basal ganglia on cortical computation: A hybrid network/neural field model. Society for Neuroscience 2012 (SFN '12).

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Sanchez, J., Lytton WW., Carmena J., Principe J., Fortes J., Barbour R., et al. (2012). Dynamically repairing and replacing neural networks: using hybrid computational and biological tools. {IEEE} Pulse. 3, 57-59.

Neymotin, S., Lytton WW., O'Connell MN., & Lakatos P. (2013). Dynamical microstates in primary auditory cortex. Society for Neuroscience Abstracts. 43,

Neymotin, S. A., Lytton WW., Oconnell M. N., & Lakatos P. (2013). Dynamical microstates in primary auditory cortex. Society for Neuroscience 2013 (SFN '13).

Lytton, WW., Contreras D., Destexhe A., & Steriade M. (1997). Dynamic interactions determine partial thalamic quiescence in a computer network model of spike-and-wave seizures. jnphys. 77, 1679-1696.

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.