Lab Publications

Found 267 results
Author Title [ Type(Asc)] Year
Conference Paper
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.
Chadderdon, GL., Neymotin SA., Kerr CC., Francis JT., & Lytton WW. (2012).  Dopamine-based reinforcement learning of virtual arm reaching task in a spiking model of motor cortex. International Conference on Cognititve and Neural Systems 16.
Chadderdon, GL., Neymotin SA., Kerr CC., Francis JT., & Lytton WW. (2012).  Dopamine-based reinforcement learning of virtual arm reaching task in a spiking model of motor cortex. Society for Neuroscience.
Fenton, A. A., Lee H., & Lytton WW. (2009).  Disinhibition can account for the neural discoordination associated with impaired cognitive control. Society for Neuroscience 2009 (SFN '09).
Kerr, CC., Fietkiewicz CT., Chadderdon GL., Neymotin SA., & Lytton WW. (2010).  Development of In Silico Brain for DARPA REPAIR project. DARPA Neural Engineering, Science, and Technology Meeting.
Kelley, C.., Dura-Bernal S.., Neymotin S.., & Lytton W.. W. (2019).  Dendritic resonance in a detailed model of pyramidal tract neuron of mouse primary motor cortex. Society for Neuroscience 2019 (SFN '19).
Gao, P., Graham J. W., Angulo S., Dura-Bernal S., Lytton WW., & Antic S. D. (2017).  Dendritic plateau generation model in cortical pyramidal neurons: A link to cortical ensembles. Society for Neuroscience 2017 (SFN '17).
Suter, B. A., Neymotin S. A., Shepherd G. M. G., & Lytton WW. (2016).  Dendritic morphology of corticospinal and crossed-corticostriatal neurons in mouse primary motor cortex. Society for Neuroscience 2016 (SFN '16).
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., Neymotin S. A., Suter B. A., Kelley C., Tekin R., Shepherd G. M. G., et al. (2019).  Cross-frequency coupling and information flow in a multiscale model of M1 microcircuits. Society for Neuroscience (SFN'19).
Francis, J. T., Chapin J., Lytton WW., Barbour R., Carmena J., Principe J., et al. (2010).  Creating the synthetic brain through hybrid computational and biological systems repairing and replacing neural networks. Society for Neuroscience 2010 (SFN '10).
Sherif, M. A., Barry J. M., Neymotin S. A., & Lytton W. W. (2012).  CPP alters theta/gamma oscillations in rat hippocampus: simulation and experiment. Computational Neuroscience Meeting (CNS 12').
Sherif, MA., Barry JM., Neymotin SA., & Lytton WW. (2012).  CPP alters hippocampal CA1 oscillations in rat: simulation and experiment. Computational Neuroscience.
Sherif, M. A., Barry J. M., Neymotin S. A., & Lytton WW. (2012).  CPP alters cross-frequency coupling between theta and gamma in CA1 in rats: Simulation and experiment. Society for Neuroscience 2012 (SFN '12).
Angulo, S., Graham J. W., Gao P., Dura-Bernal S., Neymotin S. A., Antic S. D., et al. (2017).  Cortical ensembles based on dendritic plateau generation in the prefrontal cortex. Society for Neuroscience 2017 (SFN '17).
Lytton, WW., & Shepherd G. M. G. (2010).  Computer network model predicts dependence of neocortical laminar activation patterns on form of stimulation. Society for Neuroscience 2010 (SFN '10).
Doherty, D.. W., Dura-Bernal S.., & Lytton W.. W. (2019).  Computer models of mouse area M1 show avalanches for full model and subcircuits defined by layer or cell type. Society for Neuroscience 2019 (SFN '19).
Sherif, M. A., Skosnik P., Hajs M., & Lytton WW. (2015).  Computer model of endocannabinoid effects in CA3. Society for Neuroscience 2015 (SFN '15).
Lazarewicz, M. T., Contreras D., Finkel L. H., & Lytton WW. (2009).  Computer model of a theta-gamma dissociation in hippocampus. Society for Neuroscience 2009 (SFN '09).
Kerr, C., Dura-Bernal S., Menzies R. J., Mclauchlan C., Van Albada S. J., Kedziora D. J., et al. (2016).  Computational capacity as a function of network size. Society for Neuroscience 2016 (SFN '16).
Lytton, WW., Neymotin SA., Lee HK., Uhlrich DJ., & AA F. (2008).  Circuit changes augment disinhibited shock responses in computer models of neocortex. American Epilepsy Society Annual Meeting.
Mcdougal, R. A., Hines M. L., & Lytton WW. (2012).  Calcium-electrical interactions: An example of reaction-diffusion in the neuron simulator. Society for Neuroscience 2012 (SFN '12).
Sherif, M. A., Mcdougal R., Neymotin S., Hines M., & Lytton WW. (2013).  Calcium wave propagation varies with changes in endoplasmic reticulum parameters: A computer model. Society for Neuroscience 2013 (SFN '13).
Neymotin, S. A., McDougal R. A., Hines M., & Lytton W. W. (2014).  Calcium regulation of HCN supports persistent activity associated with working memory: a multiscale model of prefrontal cortex. Computational Neuroscience Meeting (CNS 14').
Neymotin, S. A., Mcdougal R. A., Hines M. L., & Lytton WW. (2014).  Calcium regulation of HCN supports persistent activity associated with working memory: A multiscale model of prefrontal cortex. Society for Neuroscience 2014 (SFN '14).
Mcdougal, R. A., Hines M. L., & Lytton WW. (2014).  Calcium 'impedance mismatch' – the role of geometry on diffusion dynamics. Society for Neuroscience 2014 (SFN '14).
Mcdougal, R. A., Newton A., Hines M. L., & Lytton WW. (2018).  Building, simulating, and visualizing reaction-diffusion models with NEURON's enhanced rxd module. Society for Neuroscience 2018 (SFN '18).
McDougal, R. A., Newton A. J. H., & Lytton W. W. (2018).  Building and visualizing reaction–diffusion simulations in NEURON. Computational Neuroscience Meeting (CNS 18').
Lytton, WW., & Drongelen W. (2015).  Beyond the canon: temporal and spatial multiscale organization in cortex. Computational Neuroscience Meeting Workshop.
Neymotin, S. A., Dura-Bernal S., Suter B. A., Lakatos P., Shepherd G. M. G., & Lytton WW. (2016).  Beta oscillations in neocortex: A multiscale modeling study. Society for Neuroscience 2016 (SFN '16).
Neymotin, S. A., Kerr C., Francis J. T., & Lytton WW. (2011).  Attentional modulation of receptive fields in a computer model of the thalamocortical system. Society for Neuroscience 2011 (SFN '11).
Neymotin, S. A., Lee H., Park E., Fenton A. A., & Lytton W. W. (2010).  Altered information transfer in neuronal networks marks pathology. Computational Neuroscience Meeting (CNS 10').
Book Chapter
Lytton, WW., Stewart M., & Hines ML. (2008).  Simulation of large networks: technique and progress. (Soltesz, I., & Staley K., Ed.).Computational Neuroscience in Epilepsy. 3-17.
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.
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,
Lytton, WW., & Kerr C.. (2013).  Computational Neuroscience of Neurons and Synapses. (Pfaff, D., Ed.).
Neymotin, S., Mathew A.M.., Kerr C.., & Lytton WW. (2013).  Computational Neuroscience of Neuronal Networks. (Pfaff, D., Ed.).
Lytton, WW., & Sejnowski TJ. (1992).  Computational Neuroscience. (Asbury, AK., McKhann GM., & McDonald WI., Ed.).Diseases of the Nervous System: Clinical Neurobiology.
Lytton, WW. (1997).  Brain organization: from molecules to parallel processing. (Trimble, MR., & Cummings JL., Ed.).Contemporary Behavioral Neurology. 5-28.
Neymotin, S., Taxin ZH., Mohan A., & Lipton P. (2013).  Brain Ischemia and Stroke. (Jaeger, D., & Jang R., Ed.).Encyclopedia of Computational Neuroscience.
Sherif, M., & Lytton WW. (2016).  Brain Diseases. (Arbib, MA., & Bonaiuto JJ., Ed.).From Neuron to Cognition Via Computational Neuroscience. 673-692.