Lab Publications

Found 125 results
Author [ Title(Asc)] Type Year
Filters: Type is Journal Article  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
W
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Water-tight membranes from neuronal morphology files. J Neurosci Methods. 220, 167–178.
V
Lytton, WW., Neymotin S., & Hines ML. (2008).  The virtual slice setup. J Neurosci Methods. 171, 309-315.
U
Newton, A. J. H., McDougal R. A., Hines M. L., & Lytton W. W. (2018).  Using NEURON for reaction-diffusion modeling of extracellular dynamics. Frontiers in Neuroinformatics.
Lytton, WW., Williams ST., & Sober SJ. (1999).  Unmasking unmasked: Neural dynamics following stroke. Progress in Brain Research. 121, 203-218.
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.
T
Neymotin, S., Talbot ZN., Jung JQ., Fenton AA., & Lytton WW. (2017).  Tracking recurrence of correlation structure in neuronal recordings. J Neurosci Methods. 275, 1-9.
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.
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., 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.
Lytton, WW., & Omurtag A. (2007).  Tonic-clonic transitions in computer simulation. J Clin Neurophys. 24, 175-181.
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,
S
Rowan, M., & Neymotin S. (2013).  Synaptic scaling balances learning in a spiking model of neocortex. Springer LNCS. 7824, 20–29.
Neymotin, S., Jacobs KM., Fenton AA., & Lytton WW. (2011).  Synaptic information transfer in computer models of neocortical columns. J Comput Neurosci. 30, 69-84.
Neymotin, S., Olypher AV., Kao HY., Kelemen E., Jozwicka AE., Lytton WW., et al. (2008).  Standardized assessment of extracellular single unit isolation quality. socns. 690, 12.
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.
Omurtag, A., & Lytton WW. (2010).  Spectral method and high-order finite differences for the nonlinear cable equation. Neural Comput. 22, 2113-2136.
Wathey, JC., Lytton WW., Jester JM., & Sejnowski TJ. (1991).  Simulations of synaptic potentials using realistic models of hippocampal pyramidal neurons. 163, 18.
Lytton, WW., & Sejnowski TJ. (1991).  Simulations of cortical pyramidal neurons synchronized by inhibitory interneurons. 66, 1059-1079.
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.
R
Lytton, WW., & Stewart M. (2005).  A rule-based firing model for neural networks. Int. J. for Bioelectromagnetism. 7, 47-50.
Lytton, WW., & Stewart M. (2006).  Rule-based firing for network simulations. Neurocomputing. 69, 1160-1164.
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.
McDougal, R. A., Bulanova AS., & Lytton WW. (2016).  Reproducibility in computational neuroscience models and simulations. {IEEE} Trans Biomed Eng. 63, 2021-2035.
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.
Neymotin, S., Chadderdon GL., Kerr CC., Francis JT., & Lytton WW. (2013).  Reinforcement learning of 2-joint virtual arm reaching in computer model of sensorimotor cortex. Neural Comput. 25, 3263–3293.
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.
Sober, SJ., Stark JM., Yamasaki DS., & Lytton WW. (1997).  Receptive field changes following stroke-like cortical ablation: a role for activation dynamics. jnphys. 78, 3438-3443.
Lytton, WW., & Wathey J. C. (1992).  Realistic single-neuron modeling. Seminars in Neuroscience. 4, 15-25.
McDougal, R. A., Skolnick Y., Schaff JC., Lytton WW., & Hines ML. (2012).  Reaction-diffusion modeling in the NEURON simulator. BMC Neuroscience. 13, P119.
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Reaction-Diffusion in the NEURON Simulator. Front Neuroinform. 7:28,
P
Zhu, JJ., Uhlrich D., & Lytton WW. (1999).  Properties of a Hyperpolarization-Activated Cation Current in Interneurons in the Rat Lateral Geniculate Nucleus. Neuroscience. 92, 445-457.
Neville, K., & Lytton WW. (1999).  Potentiation of Ca influx through NMDA channels by action potentials: a computer model. Neuroreport. 10, 3711-3716.
Uhlrich, DJ., Manning KA., Laughlin ML., & Lytton WW. (2005).  Photic-induced sensitization: acquisition of an augmenting spike-wave response in the adult rat through repeated strobe exposure. Journal of Neurophysiology. 94, 3925-3937.
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.
Briska, AM., Uhlrich DJ., & Lytton WW. (1999).  Passive properties & signal synergy in thalamic cells. 25,
O'Laughlin, ML., Uhlrich DJ., & Lytton WW. (2004).  Paroxysm potentiation: synaptic potentiation enhances repetitive epileptiform discharge without enhancing evoked response. Computation and neural systems meeting. Abstract,
Patoary, M. Nazrul Ish, Tropper C., McDougal R. A., Lin Z., & Lytton W. W. (2019).  Parallel Stochastic Discrete Event Simulation of Calcium Dynamics in Neuron. IEEE/ACM Trans. Comput. Biol. Bioinform.. 16, 1007–1019.
Patoary, M. Nazrul Ish, Tropper C., McDougal R. A., Zhongwei L., & Lytton WW. (2017).  Parallel Stochastic discrete event simulation of calcium dynamics in neuron.. IEEE/ACM transactions on computational biology and bioinformatics.
Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.
O
Zhu, JJ., Uhlrich D., & Lytton WW. (1995).  Oscillations in Thalamic Interneurons. snabs. 21, 12.5.
Lytton, WW. (1996).  Optimizing synaptic conductance calculation for network simulations. ncomp. 8, 501-510.
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.
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.
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.
N
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.
Lytton, WW. (2006).  Neural query system: data-mining from within the NEURON simulator. Neuroinformatics. 4, 163-176.
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.
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.
M
Zhu, JJ., Uhlrich D., & Lytton WW. (1996).  Muscarinic receptor mediated responses in thalamic local interneurons. snabs. 22, 574.8.
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.
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.
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.
Lytton, WW., Neymotin S., & Kerr CC. (2014).  Multiscale modeling for clinical translation in neuropsychiatric disease. J Comput Surgery. 1, 7.
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.
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., 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.
Lytton, WW., & Thomas E. (1999).  Modeling thalamocortical oscillations. (Ulinski, P., Jones EG., & Peters A., Ed.).Cerebral Cortex. 13, 479-509.
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.
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.
Neymotin, S., Lytton WW., Olypher AO., & AA F. (2011).  Measuring the quality of neuronal identification in ensemble recordings. jnsci. 31, 16398–16409.
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.
L
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.
Lytton, WW., & Kristan WB. (1989).  Localization of a leech inhibitory synapse by photo-ablation of individual dendrites. 504, 43-48.
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.
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.
K
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.
J
Lytton, WW., Omurtag A., Neymotin S., & Hines ML. (2008).  Just-in-time connectivity for large spiking networks. ncomp. 20, 2745-2756.
I
Zhu, JJ., Lytton WW., Xue JT., & Uhlrich D. (1999).  An intrinsic oscillation in interneurons of the rat lateral geniculate nucleus. jnphys. 81, 702-711.
Neymotin, S., Lee HY., Fenton AA., & Lytton WW. (2010).  Interictal EEG Discoordination in a Rat Seizure Model. J Clin Neurophysiol. 27, 438–444.
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.
Deyo, S., & Lytton WW. (1997).  Inhibition Can Disrupt Hypersynchrony In Model Neuronal Networks. Progress in neuro-psychopharmacology & biological psychiatry.
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.