Lab Publications

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.

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.

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.

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.

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.

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).

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

Sherif, M. A., Neymotin S. A., & Lytton WW. (2016).  Schizophrenia genome-wide association studied with computer simulation: gamma oscillations and information flow in CA3. Society for Neuroscience 2016 (SFN '16).

Neymotin, SA., Kerr CC., Chadderdon GL., Francis JT., & Lytton WW. (2011).  Restoring physiological oscillations using neuroprosthetic spike-timing-dependent plasticity in computer model of neocortex. Society for Neuroscience.

Dura-Bernal, S., Li K., Brockmeier A., Kerr CC., Neymotin S., Principe J., et al. (2014).  Repairing lesions via microstimulation in a spiking network model driving a virtual arm.. Society for Neuroscience.

Li, K., Dura-Bernal S., Francis J., Lytton WW., & Principe J. (2015).  Repairing Lesions via Kernel Adaptive Inverse Control in a Biomimetic Model of Sensorimotor Cortex. Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference. 1-4.

Lytton, WW., Kerr CC., Chadderdon GL., Neymotin SA., & Francis JT. (2012).  Reinforcement learning of 2-joint virtual arm reaching in detailed cortex simulation. Neural Control of Movement.

Neymotin, S. A., Chadderdon G. L., Kerr C. C., Francis J. T., & Lytton WW. (2012).  Reinforcement learning of 2-joint virtual arm reaching in computer model of sensory and motor cortex. Society for Neuroscience 2012 (SFN '12).

Neymotin, S. A., Fenton A. A., & Lytton WW. (2010).  Recurrence of correlation structure in hippocampal neuronal ensembles during spatial behavior. Society for Neuroscience 2010 (SFN '10).

Gao, P. P., Graham J. W., Angulo S. L., Dura-Bernal S., Hines M. L., Lytton WW., et al. (2018).  Recruitment of neurons into neural ensembles based on dendritic plateau potentials. Society for Neuroscience 2018 (SFN '18).

Kerr, C., Von Kraus L., Iordanou J., Neymotin S. A., Francis J., & Lytton WW. (2013).  Receptive field formation and erasure in somatosensory cortex. Society for Neuroscience 2013 (SFN '13).

McDougal, R., Hines ML., & Lytton WW. (2012).  Reaction-diffusion modeling in the NEURON simulator. Computational Neuroscience.

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).

Tropper, C., Zhongwei L., Mcdougal R. A., Hines M., & Lytton WW. (2015).  Parallel reaction-diffusion simulation in NEURON. Society for Neuroscience 2015 (SFN '15).

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.

Kerr, C., Choi J. S., Dura-Bernal S., Francis J. T., & Lytton WW. (2014).  One size does not fit all: Calibrating microstimulation to individual subjects using spiking network models. Society for Neuroscience 2014 (SFN '14).

Mcdougal, R. A., Lytton WW., & Hines M. L. (2011).  Object-oriented reaction-diffusion modeling in the neuron simulator. Society for Neuroscience 2011 (SFN '11).

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.

Dura-Bernal, S., Suter B. A., Neymotin S. A., Quintana A., Gleeson P., Sheperd G. M. G., et al. (2015).  Normalized cortical depth (NCD) as a primary coordinate system for cell connectivity in cortex: experiment and model. Society for Neuroscience 2015 (SFN '15).

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).

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., 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).