Lab Publications | Neurosim lab

Found 267 results

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

Lytton, WW., & Shepherd G. M. G. (2010). Computer network model predicts dependence of neocortical laminar activation patterns on form of stimulation. Society for Neuroscience 2010 (SFN '10).

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

Lytton, WW., & Kerr C.. (2013). Computational Neuroscience of Neurons and Synapses. (Pfaff, D., Ed.).

Lytton, WW., Stewart M., & Hines ML. (2008). Simulation of large networks: technique and progress. (Soltesz, I., & Staley K., Ed.).Computational Neuroscience in Epilepsy. 3-17.

Lytton, WW., Williams ST., & Sober SJ. (1999). Unmasking unmasked: Neural dynamics following stroke. Progress in Brain Research. 121, 203-218.

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

Lytton, WW., Vadigepalli R., & Kramer MA. (2015). Multiscale Computational Modeling for the US BRAIN initiative.

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., 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., & Stewart M. (2005). A rule-based firing model for neural networks. Int. J. for Bioelectromagnetism. 7, 47-50.

Lytton, WW. (2018). Multiscale modeling of brain disease. Society for Neuroscience 2018 (SFN '18).

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

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.

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.

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.

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.

Lazarewicz, M. T., Contreras D., Finkel L. H., & Lytton WW. (2009). Computer model of a theta-gamma dissociation in hippocampus. Society for Neuroscience 2009 (SFN '09).

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.

Lakatos, P., Barczak A., Neymotin S. A., Lytton WW., Mcginnis T., Javitt D. C., et al. (2014). Thalamocortical dynamics of rhythmic selective and tonic suppressive modes in the auditory system. Society for Neuroscience 2014 (SFN '14).

K

Kubie, J. L., Fenton A. A., Lytton WW., & Burgess N. (2009). Grid-cell models for navigation and context discrimination. Society for Neuroscience 2009 (SFN '09).

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.

Kerr, CC., Fietkiewicz CT., Chadderdon GL., Neymotin SA., & Lytton WW. (2010). Development of In Silico Brain for DARPA REPAIR project. DARPA Neural Engineering, Science, and Technology Meeting.

Kerr, CC., Mo J., Neymotin SA., M D., & Lytton WW. (2011). Interlaminar Granger causality and alpha oscillations in a model of macaque cortex. Computational Neuroscience.

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).

Kerr, CC., Neymotin SA., Mo J., Schroeder CE., M D., & Lytton WW. (2011). Interlaminar feedback connections dominate in macaque inferotemporal cortex: in vivo and in silico studies. Society for Neuroscience.

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, C., Dura-Bernal S., Menzies R. J., Mclauchlan C., Van Albada S. J., Kedziora D. J., et al. (2016). Computational capacity as a function of network size. Society for Neuroscience 2016 (SFN '16).

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, C., Van Albada S. J., Neymotin S. A., Chadderdon G. L., Robinson P. A., & Lytton WW. (2012). Effects of basal ganglia on cortical computation: A hybrid network/neural field model. Society for Neuroscience 2012 (SFN '12).

Kerr, CC., Neymotin SA., Song W., Francis JT., & Lytton WW. (2011). Modulation of stimulus fields in a computer model of the thalamocortical system. Society for Neuroscience.

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, 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).

Kerr, C., Choi J. S., Dura-Bernal S., Francis J. T., & Lytton WW. (2014). One size does not fit all: Calibrating microstimulation to individual subjects using spiking network models. Society for Neuroscience 2014 (SFN '14).

Kerr, CC., van Albada SJ., Chadderdon GL., Neymotin SA., Robinson PA., & Lytton WW. (2012). Effects of basal ganglia on cortical computation: a hybrid network/neural field model. Society for Neuroscience.

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.

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.

Kelley, C.., Dura-Bernal S.., Neymotin S.., & Lytton W.. W. (2019). Dendritic resonance in a detailed model of pyramidal tract neuron of mouse primary motor cortex. Society for Neuroscience 2019 (SFN '19).

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.

J

Johnson, D. H., Jung R., & Ernst U. (2009). Computational Neuroscience (CNS*2009). BMC Neuroscience. 10, I1.

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.

Holmes, W. R., Jung R., & Skinner F. (2007). Computational Neuroscience (CNS*2007). BMC Neuroscience. 8, I1.

Holmes, W. R., Jung R., & Roberts P. (2008). Computational Neuroscience (CNS*2008). BMC Neuroscience. 9, I1.

Hines, M. L., Mcdougal R., Neymotin S. A., Tropper C., & Lytton WW. (2013). Interfaces in multiscale reaction-diffusion models in the NEURON simulator. Society for Neuroscience 2013 (SFN '13).

Hilscher, M. M., Moulin T., Skolnick Y., Lytton W. W., & Neymotin S. A. (2012). Ih modulates theta rhythm and synchrony in computer model of CA3. Computational Neuroscience Meeting (CNS 12').

G

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.

Graham, J. W., Angulo S., Gao P. P., Dura-Bernal S., Sivagnanam S., Hines M.., et al. (2018). Embedded ensemble encoding: A hypothesis for reconciling cortical coding strategies. Society for Neuroscience 2018 (SFN '18).

Graham, J.. W., Gao P.. P., Dura-Bernal S.., Sivagnanam S.., Hines M.. L., Antic S.. D., et al. (2019). Modeling network effects of dendritic plateau potentials in cortical pyramidal neurons. Society for Neuroscience 2019 (SFN '19).

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.

Gleeson, P., Marin B., Sadeh S., Quintana A., Cantarelli M., Dura-Bernal S., et al. (2016). A set of curated cortical models at multiple scales on Open Source Brain. Computational Neuroscience Meeting (CNS 16').

Gao, P., Graham J. W., Angulo S., Dura-Bernal S., Lytton WW., & Antic S. D. (2017). Dendritic plateau generation model in cortical pyramidal neurons: A link to cortical ensembles. Society for Neuroscience 2017 (SFN '17).

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).

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').

F

Francis, J. T., Chapin J., Lytton WW., Barbour R., Carmena J., Principe J., et al. (2010). Creating the synthetic brain through hybrid computational and biological systems repairing and replacing neural networks. Society for Neuroscience 2010 (SFN '10).

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.

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.

Fenton, A. A., Lee H., & Lytton WW. (2009). Disinhibition can account for the neural discoordination associated with impaired cognitive control. Society for Neuroscience 2009 (SFN '09).

E

Erdemir, A., Mulugeta L., & Lytton WW. (2015). Ten "not so simple" rules for credible practice of modeling & simulation in healthcare. Frontiers in Medical Devices Meeting.

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.

D

Dura-Bernal, S., Zhou X., Chadderdon G. L., Przekwas A., & Lytton WW. (2013). Interfacing a biomimetic model of sensorimotor cortex with a musculoskeletal model and a robotic arm. Society for Neuroscience 2013 (SFN '13).

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.

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., 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., 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., Prins N., Neymotin S., Prasad A., Sanchez J., Francis JT., et al. (2014). Evaluating Hebbian reinforcement learning BMI using an in silico brain model and a virtual musculoskeletal arm.. Neural Control of Movement.

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).

Dura-Bernal, S., Menzies R. J., McLauchlan C., van Albada S. J., Kedziora D. J., Neymotin S., et al. (2016). Effect of network size on computational capacity. Computational Neuroscience Meeting (CNS 16').

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.