Lab Publications

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.

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

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

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

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.

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

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

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

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., 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. (1996).  Computer network model of mossy fiber sprouting in dentate gyrus. Epilepsia – AES Proceedings. 37 S. 5, 117.

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

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

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

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.

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

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,

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,

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.

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

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

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

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.

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

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.

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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

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

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

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.

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

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.

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

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

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

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.

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.

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.

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

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.

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.

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

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.

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.

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

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.

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.

Dura-Bernal, S., Garreau G., Georgiou J., Andreou A. G., Denham S. L., & Wennekers T. (2013).  Multimodal integration of micro-Doppler sonar and auditory signals for behavior classification with convolutional networks. International Journal of Neural Systems. 23, 1350021.

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

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.

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.

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.

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

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.

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.

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

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.

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.

Kerr, C. C., Dura-Bernal S., Smolinski T. G., Chadderdon G. L., & Wilson D. P. (2018).  Optimization by Adaptive Stochastic Descent. PLOS ONE. 13, 1-16.

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.

Lytton, WW. (1996).  Optimizing synaptic conductance calculation for network simulations. ncomp. 8, 501-510.

Zhu, JJ., Uhlrich D., & Lytton WW. (1995).  Oscillations in Thalamic Interneurons. snabs. 21, 12.5.

Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.