Lab Publications

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Found 53 results
Author Title [ Type(Desc)] Year
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Conference Paper
Neymotin, S. A., Dura-Bernal S., Suter B. A., Lakatos P., Shepherd G. M. G., & Lytton WW. (2016).  Beta oscillations in neocortex: A multiscale modeling study. Society for Neuroscience 2016 (SFN '16).
Kerr, C., Dura-Bernal S., Menzies R. J., Mclauchlan C., Van Albada S. J., Kedziora D. J., et al. (2016).  Computational capacity as a function of network size. Society for Neuroscience 2016 (SFN '16).
Angulo, S., Graham J. W., Gao P., Dura-Bernal S., Neymotin S. A., Antic S. D., et al. (2017).  Cortical ensembles based on dendritic plateau generation in the prefrontal cortex. Society for Neuroscience 2017 (SFN '17).
Dura-Bernal, S., Neymotin S. A., Suter B. A., Kelley C., Tekin R., Shepherd G. M. G., et al. (2019).  Cross-frequency coupling and information flow in a multiscale model of M1 microcircuits. Society for Neuroscience (SFN'19).
Dura-Bernal, S., Griffith E. Y., Marczak A., O'Connell N., McGinnis T., Lytton W. W., et al. (2019).  Data-driven model of auditory thalamocortical system rhythms. Society for Neuroscience (SFN '19).
Gao, P., Graham J. W., Angulo S., Dura-Bernal S., Lytton WW., & Antic S. D. (2017).  Dendritic plateau generation model in cortical pyramidal neurons: A link to cortical ensembles. Society for Neuroscience 2017 (SFN '17).
Dura-Bernal, S., Majumdar A., Neymotin S., Sivagnanam S., Francis J. T., & Lytton WW. (2015).  A dynamic data-driven approach to closed-loop neuroprosthetics based on multiscale biomimetic brain models. IEEE Interanationl Conference on High Performance Computing 2015 Workshop: InfoSymbiotics/Dynamic Data Driven Applications Systems (DDDAS) for Smarter Systems, Bangalore, India.
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').
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).
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.
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').
Dura-Bernal, S., Garreau G., Andreou C. M., Andreou A. G., Georgiou J., Wennekers T., et al. (2011).  Human Action Categorization Using Ultrasound Micro-Doppler Signatures. HBU.
Doherty, D. W., Dura-Bernal S., Neymotin S. A., & Lytton WW. (2018).  Identifying avalanches in simulated mouse primary motor cortex (M1). Society for Neuroscience 2018 (SFN '18).
Tepper, Á., Sugi A., Lytton W. W., & Dura-Bernal S. (2018).  Implementation of Cmicrocircuits model in NetPyNE and exploration of the effect of neuronal/synaptic loss on memory recall. Computational Neuroscience Meeting (CNS 18').
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).
Dura-Bernal, S., Kerr C., Neymotin S., Suter B., Shepherd G., Francis J., et al. (2015).  Large-scale M1 microcircuit model with plastic input connections from biological PMd neurons used for prosthetic arm control. 24th Annual Computational Neuroscience Meeting (CNS15).
Dura-Bernal, S., Neymotin S. A., Suter B. A., Shepherd G. M., & Lytton WW. (2017).  Long-range inputs and H-current regulate different modes of operation in a multiscale model of mouse M1 microcircuits. Society for Neuroscience 2017 (SFN '17).
Neymotin, S. A., Dura-Bernal S., Seidenstein A., Lakatos P., Sanger T. D., & Lytton and. William W. (2016).  Multiscale modeling of multitarget pharmacotherapy for dystonia. Computational Neuroscience Meeting (CNS 16').
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., Neymotin S. A., Kerr C. C., Quintana A., Gleeson P., et al. (2016).  NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks. Computational Neuroscience Meeting (CNS 16').
Dura-Bernal, S., BA S., Kerr C. C., Quintana A., Gleeson P., Shepherd GMG., et al. (2016).  NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks. Computational Neuroscience.
Kerr, C. C., O'Shea D. J., Goo W., Dura-Bernal S., Francis J. T., Diester I., et al. (2014).  Network-level effects of optogenetic stimulation in a computer model of macaque primary motor cortex. Computational Neuroscience Meeting (CNS 14').
Dura-Bernal, S., Suter B. A., Neymotin S. A., Quintana A., Gleeson P., Sheperd G. M. G., et al. (2015).  Normalized cortical depth (NCD) as a primary coordinate system for cell connectivity in cortex: experiment and model. Society for Neuroscience 2015 (SFN '15).
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).
Gao, P. P., Graham J. W., Angulo S. L., Dura-Bernal S., Hines M. L., Lytton WW., et al. (2018).  Recruitment of neurons into neural ensembles based on dendritic plateau potentials. Society for Neuroscience 2018 (SFN '18).
Gao, P., Graham J., Angulo S., Dura-Bernal S., Hines M., Lytton W. W., et al. (2018).  Recruitment of neurons into neural ensembles based on dendritic plateau potentials. Computational Neuroscience Meeting (CNS 18').
Li, K., Dura-Bernal S., Francis J., Lytton WW., & Principe J. (2015).  Repairing Lesions via Kernel Adaptive Inverse Control in a Biomimetic Model of Sensorimotor Cortex. Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference. 1-4.
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.
Dura-Bernal, S., Wennekers T.., & Denham S.. (2010).  The role of feedback in a hierarchical model of object perception. Proceedings of BICS 2010 - Brain Inspired Cognitive Systems 14-16 July 2010, Madrid, Spain..
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').
Doherty, D., Sivagnanam S., Dura-Bernal S., & Lytton W. W. (2018).  Simulation of avalanches in mouse primary motor cortex (M1). Computational Neuroscience Meeting (CNS 18').
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.
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.
Journal Article
Neymotin, S., Dura-Bernal S., Moreno H., & Lytton WW. (2017).  Computer modeling for pharmacological treatments for dystonia. Drug Discov Today: Dis Model. In Press.
Dura-Bernal, S., Zhou X., Neymotin S., Przekwas A., Francis J. T., & Lytton WW. (2015).  Cortical spiking network interfaced with virtual musculoskeletal arm and robotic arm. Frontiers in Neurorobotics. 9,
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.
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.
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.
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.
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.
Neymotin, S., Dura-Bernal S., Lakatos P., Sanger TD., & Lytton WW. (2016).  Multitarget multiscale simulation for pharmacological treatment of dystonia in motor cortex. Front Pharmacol. 7, 157.
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.
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.
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.
Dura-Bernal, S., Li K., Neymotin S., Francis JT., Principe JC., & Lytton WW. (2016).  Restoring behavior via inverse neurocontroller in a lesioned cortical spiking model driving a virtual arm. Front Neurosci. 10, 28.
Lytton, WW., Seidenstein AH., Dura-Bernal S., McDougal R. A., Schürmann F., & Hines ML. (2016).  Simulation neurotechnologies for advancing brain research: parallelizing large networks in NEURON. Neural Comput. 28, 2063-2090.
Dura-Bernal, S., Wennekers T., & Denham S. L. (2012).  Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation. PLoS One. 7, e48216.
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.