Lab Publications

Found 20 results
Author Title Type [ Year(Desc)]
Filters: First Letter Of Last Name is C  [Clear All Filters]
1997
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.
2001
Chover, J., Haberly L., & Lytton WW. (2001).  Alternating dominance of NMDA and AMPA for learning and recall: a computer model. Neuroreport. 12, 2503-2507.
2006
Migliore, M., Cannia C., Lytton WW., & Hines ML. (2006).  Parallel Network Simulations with NEURON. J. Computational Neuroscience. 6, 119-129.
2008
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.
2011
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.
2012
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.
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.
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.
2013
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.
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.
2014
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., 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.
2018
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.
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.
2019
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.