Lab Publications

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.

Sanjay, M., Neymotin S., & Babu KS. (2015).  Impaired dendritic inhibition leads to epileptic activity in a computer model of CA3. Hippocampus. in press.

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.

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.

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., 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.

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.

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.

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..

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.

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,

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.

Lytton, WW., & Brust JC. (1989).  Direct dyslexia: Preserved oral reading of real words in Wernicke's aphasia. Brain. 112, 583-594.

Lytton, WW., & Stewart M. (2002).  Dendritic resonance in in subicular dendrites, a computer model. 28,

Lytton, WW., & Stewart M. (2007).  Data mining through simulation. Methods Mol Biol. 401, 155-166.

Neymotin, S., Uhlrich DJ., Manning KA., & Lytton WW. (2008).  Data mining of time-domain features from neural extracellular field data. Studies in Computational Intelligence. 151, 119-140.

Mulugeta, L., Drach A., Erdemir A., Hunt C. A., Horner M., Ku J. P., et al. (2018).  Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience. Front. Neuroinform.. 12,

Dura-Bernal, S., Zhou X., Neymotin S., Przekwas A., Francis J. T., & Lytton WW. (2015).  Cortical spiking network interfaced with virtual musculoskeletal arm and robotic arm. Frontiers in Neurorobotics. 9,

Song, W., Kerr CC., Lytton WW., & Francis JT. (2013).  Cortical plasticity induced by spike-triggered microstimulation in primate somatosensory cortex. PLoS One. 8, e57453.

Kerr, CC., van Albada SJ., Neymotin S., Chadderdon GL., Robinson PA., & Lytton WW. (2013).  Cortical information flow in Parkinson's disease: a composite network/field model. Front Comput Neurosci. 7, 39.

Lytton, WW., Destexhe A., & Sejnowski TJ. (1996).  Control of slow oscillations in the thalamocortical neuron: A computer model. Neuroscience. 70, 673-684.

Lytton, WW. (2017).  Computers, causality and cure in epilepsy. Brain. 140, 516-519.

Wathey, JC., Lytton WW., Jester JM., & Sejnowski TJ. (1992).  Computer simulations of EPSP-to-spike (E-S) potentiation in hippocampal CA1 pyramidal cells. 12, 607-618.

Lytton, WW., Orman R., & Stewart M. (2005).  Computer simulation of epilepsy: implications for seizure spread and behavioral dysfunction. Epilepsy & Behavior. 7, 336-344.

Lytton, WW., Hellman KM., & Sutula TP. (1996).  Computer network model of mossy fiber sprouting in dentate gyrus. Epilepsia – AES Proceedings. 37 S. 5, 117.

Lytton, WW., Stark JM., Yamasaki DS., & Sober SJ. (1999).  Computer models of stroke recovery: Implications for neurorehabilitation. The Neuroscientist. 5, 100-111.

Lytton, WW., Hellman KM., & Sutula TP. (1998).  Computer Models of Hippocampal Circuit Changes of the Kindling Model of Epilepsy. Artificial Intelligence in Medicine. 13, 81-98.

Lytton, WW. (2008).  Computer modelling of epilepsy. Nat Rev Neurosci. 9, 626-637.

Newton, AJH., & Lytton WW. (2017).  Computer modeling of ischemic stroke. Drug Discov Today: Dis Model. 30, In press.

Seidenstein, AH., Barone FC., & Lytton WW. (2015).  Computer modeling of ischemic stroke. Scholarpedia. 10, 32015; revision \#148671; Accessed Oct 12, 2015.

Lytton, WW. (2017).  Computer modeling of epilepsy: opportunities for drug discovery. Drug Discov Today: Dis Model. In press.

Neymotin, S., Dura-Bernal S., Moreno H., & Lytton WW. (2017).  Computer modeling for pharmacological treatments for dystonia. Drug Discov Today: Dis Model. In Press.

Briska, AM., Uhlrich DJ., & Lytton WW. (2003).  Computer model of passive signal integration based on whole-cell ınvit\ studies of rat lateral geniculate nucleus. European Journal of Neuroscience. 17, 1531-1541.

Lytton, WW., & Sejnowski TJ. (1992).  Computer model of ethosuximide's effect on a thalamic neuron. 32, 131-139.

Lytton, WW. (1997).  A computer model of clonazepam's effect in a thalamic slice model of absence epilepsy. Neuroreport. 8, 3339-3343.

Thomas, E., & Lytton WW. (1998).  Computer model of antiepileptic effects mediated by alterations in \gabaa\-mediated inhibition. Neuroreport. 9, 691-696.

Günay, C., Smolinski TG., Lytton WW., Morse TM., Gleeson P., Crook S., et al. (2008).  Computational Intelligence in Electrophysiology. Studies in Computational Intelligence. 122, 325-359.

Eguchi, A., Neymotin S., & Stringer SM. (2014).  Color opponent receptive fields self-organize in a biophysical model of visual cortex via spike-timing dependent plasticity. Front Neural Circuits. 8, 16.

Lytton, WW., Neymotin S., Lee HY., Uhlrich DJ., & Fenton AA. (2008).  Circuit changes augment disinhibited shock responses in computer models of neocortex. American Epilepsy Society Annual Meeting. 3, 284.

Lytton, WW., & Lipton P. (1999).  Can the hippocampus tell time?: The temporo-septal engram shift model. Neuroreport. 10, 2301-2306.

Neymotin, S., McDougal R. A., Hines ML., & Lytton WW. (2014).  Calcium regulation of HCN supports persistent activity associated with working memory: a multiscale model of prefrontal cortex. BMC Neuroscience. 15, P108.

Neymotin, S., McDougal R. A., Bulanova AS., Zeki M., Lakatos P., Terman D., et al. (2016).  Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex. Neurosci. 316, 344-366.

Zhu, JJ., Uhlrich D., & Lytton WW. (1999).  Burst Firing in Identified Interneurons of the Rat Lateral Geniculate Nucleus. Neuroscience. 91, 1445-1460.

Lytton, WW., Orman R., & Stewart M. (2008).  Broadening of activity with flow across neural structures. Perception. 37, 401-407.

Fenton, AA., Lytton WW., Barry JM., Lenck-Santini PP., Zinyuk LE., Kubík S., et al. (2010).  Attention-like modulation of hippocampus place cell discharge. J Neurosci. 30, 4613-4625.

Angulo, S. L., Henzi T., Neymotin S. A., Suarez M. D., Lytton W. W., Schwaller B., et al. (2019).  Amyloid pathology–produced unexpected modifications of calcium homeostasis in hippocampal subicular dendrites. Alzheimers. Dement..

Chover, J., Haberly L., & Lytton WW. (2001).  Alternating dominance of NMDA and AMPA for learning and recall: a computer model. Neuroreport. 12, 2503-2507.

Lytton, WW. (1998).  Adapting a feedforward heteroassociative network to Hodgkin-Huxley dynamics. J. Computational Neuroscience. 5, 353-364.

Johnson, D. H., Jung R., & Ernst U. (2009).  Computational Neuroscience (CNS*2009). BMC Neuroscience. 10, I1.

Holmes, W. R., Jung R., & Roberts P. (2008).  Computational Neuroscience (CNS*2008). BMC Neuroscience. 9, I1.

Holmes, W. R., Jung R., & Skinner F. (2007).  Computational Neuroscience (CNS*2007). BMC Neuroscience. 8, I1.

Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.

Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.

Neymotin, SA., Uhlrich DJ., & Lytton WW. (2008).  Virtual slice simulation of resonance in a layered cortical model. Society for Neuroscience.

Dura-Bernal, S., Chadderdon G.L.., Neymotin S., Zhou X., Przekwas A.., Francis J.T.., et al. (2013).  Virtual musculoskeletal arm and robotic arm driven by a biomimetic model of sensorimotor cortex with reinforcement learning. Signal Processing in Medicine and Biology Symposium (SPMB), 2013 IEEE. 1-5.

Bernard, C. (2018).  Understanding epilepsy across spatial and time scales. Society for Neuroscience 2018 (SFN '18).

Olypher, A. V., Lytton W. W., & Prinz A. A. (2010).  Transformation of inputs in a model of the rat hippocampal CA1 network. Computational Neuroscience Meeting (CNS 10').

Olypher, A. V., Lytton WW., & Prinz A. A. (2010).  Transformation of inputs in a model of the rat hippocampal CA1 network. Society for Neuroscience 2010 (SFN '10).

Neymotin, S., Kerr CC., Francis JT., & Lytton WW. (2011).  Training oscillatory dynamics with spike-timing-dependent plasticity in a computer model of neocortex. 2011 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). 1–6.

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).

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).

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.

Tropper, C., Pataory M., Mcdougal R., Hines M., & Lytton WW. (2014).  Stochastic diffusion simulation in NEURON. Society for Neuroscience 2014 (SFN '14).

Neymotin, SA., Olypher AV., Kao HY., Kelemen E., Jozwicka AE., Lytton WW., et al. (2008).  Standardized assessment of extracellular single unit isolation quality. Society for Neuroscience.

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.

Neymotin, SA., Kerr CC., Fietkiewicz CT., Chadderdon GL., & Lytton WW. (2011).  Spike-timing-dependent plasticity and subcortical waves enhance alpha oscillations in a computer model of neocortex. Neuroinformatics.

Lytton, WW., Knox A., & Rosenthal J. J. C. (2017).  Site-directed mRNA editing of sodium channels has potential to alter neuronal firing and network dynamics: Computer models. Society for Neuroscience 2017 (SFN '17).

Doherty, D., Sivagnanam S., Dura-Bernal S., & Lytton W. W. (2018).  Simulation of avalanches in mouse primary motor cortex (M1). Computational Neuroscience Meeting (CNS 18').

Neymotin, SA., Wester JC., Contreras D., & Lytton WW. (2011).  Simulating the spread of activation in neocortical circuits. Computational Neuroscience. Computational Neuroscience.

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').