Lab Publications

Found 267 results
Author [ Title(Desc)] Type Year
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 
M
Seidenstein, A., Mcdougal R. A., Hines M. L., & Lytton WW. (2016).  Mosaic multiscale computer modeling of ischemic stroke. Society for Neuroscience 2016 (SFN '16).
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.
Neymotin, SA., BA S., Migliore M., Salvador D-B., Shepherd GMG., & Lytton WW. (2015).  Motor cortex neurons: from experiment to model via evolutionary algorithms. Computational Neuroscience.
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., Vadigepalli R., & Kramer MA. (2015).  Multiscale Computational Modeling for the US BRAIN initiative.
Seidenstein, A., Newton A., Macdougal R. A., & Lytton WW. (2017).  Multiscale computer modeling of penumbral zones in brain ischemia. Society for Neuroscience 2017 (SFN '17).
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.
Lytton, WW. (2018).  Multiscale modeling of brain disease. Society for Neuroscience 2018 (SFN '18).
Kerr, C. C., Van Albada S. J., Neymotin S. A., Chadderdon, Iii G. L., Robinson P. A., & Lytton W. W. (2013).  Multiscale modeling of cortical information flow in Parkinson's disease. Computational Neuroscience Meeting (CNS '13).
Neymotin, S. A., Dura-Bernal S., Seidenstein A., Lakatos P., Sanger T. D., & Lytton and. William W. (2016).  Multiscale modeling of multitarget pharmacotherapy for dystonia. Computational Neuroscience Meeting (CNS 16').
Newton, A., Seidenstein A. H., Hines M. L., Mcdougal R. A., & Lytton WW. (2018).  Multiscale simulation of spreading depolarization in ischemic stroke. Society for Neuroscience 2018 (SFN '18).
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.
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Lytton, WW., Neymotin S., Wester JC., & Contreras D. (2014).  Neocortical simulation for epilepsy surgery guidance: localization and intervention. (Bass, B., & Garbey M., Ed.).Computational Surgery and Dual Training. 339–349.
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).
Dura-Bernal, S., Gleeson P., Neymotin S., Suter B. A., Quintana A., Cantarelli M., et al. (2018).  NetPyNE: a high-level interface to NEURON to facilitate the development, parallel simulation and analysis of data-driven multiscale network models. Computational Neuroscience Meeting (CNS 18').
Dura-Bernal, S., Suter B. A., Neymotin S. A., Kerr C. C., Quintana A., Gleeson P., et al. (2016).  NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks. Computational Neuroscience Meeting (CNS 16').
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., 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.
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).
Kerr, C. C., O'Shea D. J., Goo W., Dura-Bernal S., Francis J. T., Diester I., et al. (2014).  Network-level effects of optogenetic stimulation in a computer model of macaque primary motor cortex. Computational Neuroscience Meeting (CNS 14').
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.
Park, E.., Neymotin S.., Lytton W.., & Fenton A.. A. (2009).  Neural discoordination of hippocampus and prefrontal cortex spike trains in a phencyclidine schizophrenia-related animal model. Society for Neuroscience 2009 (SFN '09).
Lytton, WW. (2006).  Neural query system: data-mining from within the NEURON simulator. Neuroinformatics. 4, 163-176.
Patoary, M. Nazrul Ish, Tropper C., Lin Z., McDougal R. A., & Lytton WW. (2014).  Neuron time warp. Simulation Conference (WSC), 2014 Winter. 3447–3458.
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.
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).
Dura-Bernal, S., Gleeson P., Kerr C., Graham J., Quintana A., & Lytton WW. (2018).  Neurosim-lab/netpyne: v0.7.7.
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).
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.
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Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.
Tropper, C., Zhongwei L., Mcdougal R. A., Hines M., & Lytton WW. (2015).  Parallel reaction-diffusion simulation in NEURON. Society for Neuroscience 2015 (SFN '15).
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.
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).
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).
Seidenstein, A. H., McDougal R. A., Hines M. L., & Lytton WW. (2015).  Parallelizing large networks using NEURON-Python. BMC Neuroscience.
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,
Briska, AM., Uhlrich DJ., & Lytton WW. (1999).  Passive properties & signal synergy in thalamic cells. 25,
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.
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.
Neville, K., & Lytton WW. (1999).  Potentiation of Ca influx through NMDA channels by action potentials: a computer model. Neuroreport. 10, 3711-3716.
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.
R
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Reaction-Diffusion in the NEURON Simulator. Front Neuroinform. 7:28,
McDougal, R., Hines ML., & Lytton WW. (2012).  Reaction-diffusion modeling in the NEURON simulator. Computational Neuroscience.
McDougal, R. A., Skolnick Y., Schaff JC., Lytton WW., & Hines ML. (2012).  Reaction-diffusion modeling in the NEURON simulator. BMC Neuroscience. 13, P119.
Lytton, WW., & Wathey J. C. (1992).  Realistic single-neuron modeling. Seminars in Neuroscience. 4, 15-25.
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.
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).
Gao, P., Graham J., Angulo S., Dura-Bernal S., Hines M., Lytton W. W., et al. (2018).  Recruitment of neurons into neural ensembles based on dendritic plateau potentials. Computational Neuroscience Meeting (CNS 18').
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).
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).
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.
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., 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.
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 W. W. (2012).  Reinforcement learning of 2-joint virtual arm reaching in motor cortex simulation. Computational Neuroscience Meeting (CNS '12).
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.
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.
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.
McDougal, R. A., Bulanova AS., & Lytton WW. (2016).  Reproducibility in computational neuroscience models and simulations. {IEEE} Trans Biomed Eng. 63, 2021-2035.
Dura-Bernal, S.., Neymotin S.. A., Suter B.. A., Kelley C.., Tekin R.., Shepherd G.. M., et al. (2019).  Response to simultaneous long-range inputs and oscillatory inputs in a multiscale model of M1 microcircuits. Society for Neuroscience 2019 (SFN '19).
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.
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., Wennekers T.., & Denham S.. (2010).  The role of feedback in a hierarchical model of object perception. Proceedings of BICS 2010 - Brain Inspired Cognitive Systems 14-16 July 2010, Madrid, Spain..