Lab Publications

Found 14 results
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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').
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.
Rowan, MS., Neymotin S., & Lytton WW. (2014).  Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Front Comput Neurosci. 8, 39.
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).
Antic, S. D., Hines M., & Lytton WW. (2018).  Embedded ensemble encoding hypothesis: The role of the ``Prepared'' cell. J. Neurosci. Res..
Neymotin, S., Lee HY., Park EH., Fenton AA., & Lytton WW. (2011).  Emergence of physiological oscillation frequencies in a computer model of neocortex. Front Comput Neurosci. 5, 19.
Neymotin, SA., H L., Park EH., AA F., & Lytton WW. (2010).  Emergent oscillations in neocortex: a simulation study. Dynamical Neuroscience XVIII: The Resting Brain: Not at Rest! Satellite meeting for Society for Neuroscience Meeting.
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., 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.
Mcdougal, R. A., Tropper C., Hines M. L., & Lytton WW. (2016).  Expanding NEURON support for reaction-diffusion models. Society for Neuroscience 2016 (SFN '16).
Newton, A. J. H., Seidenstein A. H., McDougal R. A., Hines M., & Lytton W. W. (2018).  Extracellular reaction–diffusion in the NEURON simulator: modeling ischemic stroke. Computational Neuroscience Meeting (CNS 18').