Lab Publications

Found 125 results
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A
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..
Antic, S. D., Hines M., & Lytton WW. (2018).  Embedded ensemble encoding hypothesis: The role of the ``Prepared'' cell. J. Neurosci. Res..
B
Briska, AM., Uhlrich DJ., & Lytton WW. (1999).  Passive properties & signal synergy in thalamic cells. 25,
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.
Briska, AM., Uhlrich DJ., & Lytton WW. (2000).  Independent dendritic domains in the thalamic circuit. Neurocomputing. 32, 299–305.
C
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.
Chadderdon, GL., Neymotin S., Kerr CC., & Lytton WW. (2012).  Reinforcement Learning of Targeted Movement in a Spiking Neuronal Model of Motor Cortex. PLoS One. 7, e47251.
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.
Chover, J., Haberly L., & Lytton WW. (2001).  Alternating dominance of NMDA and AMPA for learning and recall: a computer model. Neuroreport. 12, 2503-2507.
D
Deyo, S., & Lytton WW. (1997).  Inhibition Can Disrupt Hypersynchrony In Model Neuronal Networks. Progress in neuro-psychopharmacology & biological psychiatry.
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,
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., Li K., Neymotin S., Francis JT., Principe JC., & Lytton WW. (2016).  Restoring behavior via inverse neurocontroller in a lesioned cortical spiking model driving a virtual arm. Front Neurosci. 10, 28.
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.
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.
Dura-Bernal, S., Chadderdon GL., Neymotin S., Francis JT., & Lytton WW. (2014).  Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm. Pattern Recognit Lett. 36, 204–212.
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.
Dura-Bernal, S., Wennekers T., & Denham S. L. (2012).  Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation. PLoS One. 7, e48216.
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.
E
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.
F
Fenton, AA., Kao HY., Neymotin S., Olypher A., Vayntrub Y., Lytton WW., et al. (2008).  Unmasking the CA1 ensemble place code by exposures to small and large environments: more place cells and multiple, irregularly arranged, and expanded place fields in the larger space. jnsci. 28, 11250-11262.
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.
Forgacs, PB., Gizycki H., Selesnick I., Syed NA., Ebrahim K., Avitable M., et al. (2008).  Perisaccadic parietal and occipital gamma power in light and in complete darkness. Perception. 37, 419-432.
G
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.
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.
H
C Hunt, A., Erdemir A., Gabhann F. Mac, Lytton WW., Sander E. A., Transtrum M. K., et al. (2018).  The Spectrum of Mechanism-oriented Models for Explanations of Biological Phenomena.
K
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.
Kapur, A., Lytton WW., Ketchum K., & Haberly L. (1997).  Regulation of the NMDA component of EPSPs by different components of postsynaptic GABAergic inhibition: A computer simulation analysis in piriform cortex. jnphys. 78, 2546-2559.
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.
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., 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.
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.
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.
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.
L
Lakatos, P., Barczak A., Neymotin S., Lytton WW., McGinnis T., Javitt D., et al. (2014).  Thalamocortical dynamics of rhythmic selective and tonic suppressive modes in the auditory system. Society for Neuroscience Abstracts. 44,
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.
Lee, GJ., Matsunaga A., Dura-Bernal S., Zhang W., Lytton WW., Francis JT., et al. (2014).  Towards real-time communication between in vivo neurophysiological data sources and simulator-based brain biomimetic models. Journal of Computational Surgery. 3, 12.
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.
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.
Lytton, WW., Neymotin S., & Kerr CC. (2014).  Multiscale modeling for clinical translation in neuropsychiatric disease. J Comput Surgery. 1, 7.
Lytton, WW. (1991).  Simulations of a phase comparing neuron of the electric fish Eigenmannia. 169, 117-125.
Lytton, WW., Seidenstein AH., Dura-Bernal S., McDougal R. A., Schürmann F., & Hines ML. (2016).  Simulation neurotechnologies for advancing brain research: parallelizing large networks in NEURON. Neural Comput. 28, 2063-2090.
Lytton, WW., & Stewart M. (2002).  Dendritic resonance in in subicular dendrites, a computer model. 28,
Lytton, WW., & Wathey J. C. (1992).  Realistic single-neuron modeling. Seminars in Neuroscience. 4, 15-25.
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., Williams ST., & Sober SJ. (1999).  Unmasking unmasked: Neural dynamics following stroke. Progress in Brain Research. 121, 203-218.
Lytton, WW., & Hines M. (2005).  Independent variable timestep integration of individual neurons for network simulations. 17, 903-921.
Lytton, WW. (2017).  Computers, causality and cure in epilepsy. Brain. 140, 516-519.
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., & Omurtag A. (2007).  Tonic-clonic transitions in computer simulation. J Clin Neurophys. 24, 175-181.
Lytton, WW., & Stewart M. (2007).  Data mining through simulation. Methods Mol Biol. 401, 155-166.
Lytton, WW., & Sejnowski TJ. (1991).  Simulations of cortical pyramidal neurons synchronized by inhibitory interneurons. 66, 1059-1079.
Lytton, WW., & Thomas E. (1999).  Modeling thalamocortical oscillations. (Ulinski, P., Jones EG., & Peters A., Ed.).Cerebral Cortex. 13, 479-509.
Lytton, WW., Stark JM., Yamasaki DS., & Sober SJ. (1999).  Computer models of stroke recovery: Implications for neurorehabilitation. The Neuroscientist. 5, 100-111.
Lytton, WW., Neymotin S., & Hines ML. (2008).  The virtual slice setup. J Neurosci Methods. 171, 309-315.
Lytton, WW. (2017).  Computer modeling of epilepsy: opportunities for drug discovery. Drug Discov Today: Dis Model. In press.
Lytton, WW., & Stewart M. (2005).  A rule-based firing model for neural networks. Int. J. for Bioelectromagnetism. 7, 47-50.
Lytton, WW. (2008).  Computer modelling of epilepsy. Nat Rev Neurosci. 9, 626-637.
Lytton, WW., & Kristan WB. (1989).  Localization of a leech inhibitory synapse by photo-ablation of individual dendrites. 504, 43-48.
Lytton, WW., Destexhe A., & Sejnowski TJ. (1996).  Control of slow oscillations in the thalamocortical neuron: A computer model. Neuroscience. 70, 673-684.
Lytton, WW. (1997).  A computer model of clonazepam's effect in a thalamic slice model of absence epilepsy. Neuroreport. 8, 3339-3343.
Lytton, WW., & Stewart M. (2006).  Rule-based firing for network simulations. Neurocomputing. 69, 1160-1164.
Lytton, WW., Omurtag A., Neymotin S., & Hines ML. (2008).  Just-in-time connectivity for large spiking networks. ncomp. 20, 2745-2756.
Lytton, WW., & Brust JC. (1989).  Direct dyslexia: Preserved oral reading of real words in Wernicke's aphasia. Brain. 112, 583-594.
Lytton, WW., & Lipton P. (1999).  Can the hippocampus tell time?: The temporo-septal engram shift model. Neuroreport. 10, 2301-2306.
Lytton, WW. (1996).  Optimizing synaptic conductance calculation for network simulations. ncomp. 8, 501-510.
Lytton, WW. (1998).  Adapting a feedforward heteroassociative network to Hodgkin-Huxley dynamics. J. Computational Neuroscience. 5, 353-364.
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., & Sejnowski TJ. (1992).  Computer model of ethosuximide's effect on a thalamic neuron. 32, 131-139.
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. (2006).  Neural query system: data-mining from within the NEURON simulator. Neuroinformatics. 4, 163-176.
Lytton, WW., Orman R., & Stewart M. (2008).  Broadening of activity with flow across neural structures. Perception. 37, 401-407.
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.
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., 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.