Lab Publications

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Found 125 results
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2018
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,
Antic, S. D., Hines M., & Lytton WW. (2018).  Embedded ensemble encoding hypothesis: The role of the ``Prepared'' cell. J. Neurosci. Res..
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.
Dura-Bernal, S., Neymotin S., Suter BA., Shepherd GMG., & Lytton WW. (2018).  Long-range inputs and H-current regulate different modes of operation in a multiscale model of mouse M1 microcircuits. bioRxiv.
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.
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.
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.
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.
2017
Neymotin, S., Dura-Bernal S., Moreno H., & Lytton WW. (2017).  Computer modeling for pharmacological treatments for dystonia. Drug Discov Today: Dis Model. In Press.
Lytton, WW. (2017).  Computer modeling of epilepsy: opportunities for drug discovery. Drug Discov Today: Dis Model. In press.
Newton, AJH., & Lytton WW. (2017).  Computer modeling of ischemic stroke. Drug Discov Today: Dis Model. 30, In press.
Lytton, WW. (2017).  Computers, causality and cure in epilepsy. Brain. 140, 516-519.
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.
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.
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.
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.
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.
Neymotin, S., Suter BA., Dura-Bernal S., Shepherd GM., Migliore M., & Lytton WW. (2017).  Optimizing computer models of corticospinal neurons to replicate in vitro dynamics. J Neurophysiol. 117, 148-162.
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.
Neymotin, S., Talbot ZN., Jung JQ., Fenton AA., & Lytton WW. (2017).  Tracking recurrence of correlation structure in neuronal recordings. J Neurosci Methods. 275, 1-9.
2014
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.
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.
Rowan, MS., Neymotin S., & Lytton WW. (2014).  Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Front Comput Neurosci. 8, 39.
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.
Taxin, ZH., Neymotin S., Mohan A., Lipton P., & Lytton WW. (2014).  Modeling molecular pathways of neuronal ischemia. Prog Mol Biol Transl Sci. 123, 249–275.
Dura-Bernal, S., Li K., Brockmeier A., Kerr C., Neymotin S., Principe J., et al. (2014).  Modulation of virtual arm trajectories via microstimulation in a spiking model of sensorimotor cortex. BMC Neuroscience. 15, P106.
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.
Lytton, WW., Neymotin S., & Kerr CC. (2014).  Multiscale modeling for clinical translation in neuropsychiatric disease. J Comput Surgery. 1, 7.
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.
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,
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.
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.
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.
Song, W., Kerr CC., Lytton WW., & Francis JT. (2013).  Cortical plasticity induced by spike-triggered microstimulation in primate somatosensory cortex. PLoS One. 8, e57453.
Neymotin, S., Lytton WW., O'Connell MN., & Lakatos P. (2013).  Dynamical microstates in primary auditory cortex. Society for Neuroscience Abstracts. 43,
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.
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.
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Reaction-Diffusion in the NEURON Simulator. Front Neuroinform. 7:28,
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.
Rowan, M., & Neymotin S. (2013).  Synaptic scaling balances learning in a spiking model of neocortex. Springer LNCS. 7824, 20–29.
McDougal, R. A., Hines ML., & Lytton WW. (2013).  Water-tight membranes from neuronal morphology files. J Neurosci Methods. 220, 167–178.