Lab Publications

Found 60 results
Author Title Type [ Year(Asc)]
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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.
Neymotin, S. A., McDougal R. A., Hines M., & Lytton W. W. (2014).  Calcium regulation of HCN supports persistent activity associated with working memory: a multiscale model of prefrontal cortex. Computational Neuroscience Meeting (CNS 14').
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.
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.
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.
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., 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.
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.
2013
Neymotin, S., Taxin ZH., Mohan A., & Lipton P. (2013).  Brain Ischemia and Stroke. (Jaeger, D., & Jang R., Ed.).Encyclopedia of Computational Neuroscience.
Neymotin, S., Mathew A.M.., Kerr C.., & Lytton WW. (2013).  Computational Neuroscience of Neuronal Networks. (Pfaff, D., Ed.).
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., 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.
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., 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.
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.