Lab Publications

Found 28 results
Author [ Title(Desc)] Type Year
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A
Chover, J., Haberly L., & Lytton WW. (2001).  Alternating dominance of NMDA and AMPA for learning and recall: a computer model. Neuroreport. 12, 2503-2507.
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..
C
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.
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.
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., Hellman KM., & Sutula TP. (1996).  Computer network model of mossy fiber sprouting in dentate gyrus. Epilepsia – AES Proceedings. 37 S. 5, 117.
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,
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,
E
Antic, S. D., Hines M., & Lytton WW. (2018).  Embedded ensemble encoding hypothesis: The role of the ``Prepared'' cell. J. Neurosci. Res..
H
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.
I
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. (2005).  Independent variable timestep integration of individual neurons for network simulations. 17, 903-921.
J
Lytton, WW., Omurtag A., Neymotin S., & Hines ML. (2008).  Just-in-time connectivity for large spiking networks. ncomp. 20, 2745-2756.
L
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.
M
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.
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.
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.
N
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.
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.
P
Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.
R
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Reaction-Diffusion in the NEURON Simulator. Front Neuroinform. 7:28,
McDougal, R. A., Skolnick Y., Schaff JC., Lytton WW., & Hines ML. (2012).  Reaction-diffusion modeling in the NEURON simulator. BMC Neuroscience. 13, P119.
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.
S
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.
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.
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.
V
Lytton, WW., Neymotin S., & Hines ML. (2008).  The virtual slice setup. J Neurosci Methods. 171, 309-315.
W
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Water-tight membranes from neuronal morphology files. J Neurosci Methods. 220, 167–178.