Lab Publications

Found 68 results
Author [ Title(Desc)] Type Year
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Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Sharpee, T. O., Destexhe A., Kawato M., Sekulić V., Skinner F. K., Wójcik D. K., et al. (2016).  25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience. 17, 54.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
Denham, S., Poirazi P., De Schutter E., Friston K., Chan H. Ka, Nowotny T., et al. (2017).  26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1. BMC Neuroscience. 18, 58.
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Chover, J., Haberly L., & Lytton WW. (2001).  Alternating dominance of NMDA and AMPA for learning and recall: a computer model. Neuroreport. 12, 2503-2507.
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Lytton, WW. (1997).  Brain organization: from molecules to parallel processing. (Trimble, MR., & Cummings JL., Ed.).Contemporary Behavioral Neurology. 5-28.
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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.
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).
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.
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).
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).
D
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.
Chadderdon, GL., Neymotin SA., Kerr CC., Francis JT., & Lytton WW. (2012).  Dopamine-based reinforcement learning of virtual arm reaching task in a spiking model of motor cortex. International Conference on Cognititve and Neural Systems 16.
Chadderdon, GL., Neymotin SA., Kerr CC., Francis JT., & Lytton WW. (2012).  Dopamine-based reinforcement learning of virtual arm reaching task in a spiking model of motor cortex. Society for Neuroscience.
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.
Sanchez, J., Lytton WW., Carmena J., Principe J., Fortes J., Barbour R., et al. (2012).  Dynamically repairing and replacing neural networks: using hybrid computational and biological tools. {IEEE} Pulse. 3, 57-59.
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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., 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).
Newton, A.. J. H., Conte C.., Eggleston L.., Blasy E.., Hines M.. L., Lytton W.. W., et al. (2019).  Efficient in silico 3D intracellular neuron simulation. Society for Neuroscience 2019 (SFN '19).
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.
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Neymotin, S., Sherif M. A., Jung J. Q., Kabariti J. J., & Lytton WW. (2018).  Genome-wide associations of schizophrenia studied with computer simulation. (Cutsuridis, V., Graham BP., Cobb S., & Vida I., Ed.).Hippocampal Microcircuits: A Computational Modeler's Resource Book. 2,
Neymotin, S., Sherif M. A., Jung J. Q., Kabariti J. J., & Lytton WW. (2018).  Genome-wide associations of schizophrenia studied with computer simulation. (Cutsuridis, V., Graham BP., Cobb S., & Vida I., Ed.).Hippocampal Microcircuits: A Computational Modeler's Resource Book. 2,
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.
Cantarelli, M., Quintana A., Marin B., Earnshaw M., Gleeson P., Court R., et al. (2017).  Geppetto: an open source visualisation and simulation platform for neuroscience. Computational Neuroscience Meeting (CNS 17').
Cantarelli, M., Quintana A., Marin B., Earnshaw M., Gleeson P., Court R., et al. (2017).  Geppetto: an open source visualisation and simulation platform for neuroscience. Computational Neuroscience Meeting (CNS 17').
I
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).
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.
M
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.
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).
N
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., 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., 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).
O
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).
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., 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., 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., 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.
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.
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Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.
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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.
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).
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.
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.
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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').
Neymotin, SA., Wester JC., Contreras D., & Lytton WW. (2011).  Simulating the spread of activation in neocortical circuits. Computational Neuroscience. Computational Neuroscience.
Neymotin, SA., Kerr CC., Fietkiewicz CT., Chadderdon GL., & Lytton WW. (2011).  Spike-timing-dependent plasticity and subcortical waves enhance alpha oscillations in a computer model of neocortex. Neuroinformatics.
Choi, J. S., Menzies R. J., Dura-Bernal S., Francis J. T., Lytton WW., & Kerr C. C. (2015).  Spiking network modeling of neuronal dynamics in individual rats. BMC Neuroscience.
T
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.
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Dura-Bernal, S., Chadderdon G.L.., Neymotin S., Zhou X., Przekwas A.., Francis J.T.., et al. (2013).  Virtual musculoskeletal arm and robotic arm driven by a biomimetic model of sensorimotor cortex with reinforcement learning. Signal Processing in Medicine and Biology Symposium (SPMB), 2013 IEEE. 1-5.