Articles in Refereed Journals

Sieling FH, Archila S, Canavier CC, Prinz AA (submitted). Analysis of mixed ensembles using phase response theory.

Maran SK, Sieling FH, Demla K, Prinz AA, Canavier CC (2011). Responses of a bursting pacemaker to excitation reveal spatial segregation between bursting and spiking mechanisms. J Comput Neurosci DOI 10.1007/s10827-011-0319-y.

Sieling FH, Canavier CC, Prinz AA (2010). Inclusion of noise in iterated firing maps based on the phase response curve. Phys Rev E 81(6): 061923.

Hudson AE, Prinz AA (2010). Conductance ratios and cellular identity. PLoS Comp Biol 6(7): e1000838.

Olypher AV, Prinz AA (2010). Geometry and Dynamics of Activity-Dependent Homeostatic Regulation in Neurons. J Comp Neurosci 28: 361-374.

Gunay C, Prinz AA (2010). Model calcium sensors for network homeostasis: Sensor and readout parameter analysis from a database of model neuronal networks. J Neurosci 30: 1686-1698.

Gunay C, Edgerton JR, Li S, Sangrey T, Prinz AA, Jaeger D (2009). Database analysis of simulated and recorded electrophysiological datasets with PANDORA's Toolbox. Neuroinformatics 7: 93-111.

Canavier CC, Gurel Kazanci F, Prinz AA (2009). Phase resetting curves allow for simple and accurate prediction of robust N:1 phase locking for strongly coupled neural oscillators. Biophys J 97(1): 59-73.

Sieling FH, Canavier CC, Prinz AA (2009). Predictions of Phase-Locking in Excitatory Hybrid Networks: Excitation Does Not Promote Phase-Locking in Pattern-Generating Networks as Reliably as Inhibition. J Neurophysiol 102(1): 69-84.

Hong E., Gurel Kazanci F., Prinz A.A. (2008). Different roles of related currents in fast and slow spiking of model neurons from two phyla. J Neurophysiol. doi:10.1152/jn.90567.2008.

Langton J.T., Prinz A.A., Wittenberg D.K., Hickey T.J. (2006). Leveraging layout with dimensional stacking and pixelization to facilitate feature discovery and directed queries. Lect Notes in Comp Sci 4370: 77-91. (bibtex)

Langton J.T., Prinz A.A., Hickey T.J. (2007). NeuroVis: combining dimensional stacking and pixelization to visually explore, analyze, and mine multidimensional multivariate data. In: Proceedings of SPIE: Visualization and Data Analysis (VDA 2007) 6495: 64950H1-64950H12. (bibtex)

Smolinski T.G., Boratyn G.M., Milanova M., Buchanan R., Prinz A.A. (2006). Hybridization of independent component analysis, rough sets, and multi-objective evolutionary algorithms for classificatory decomposition of cortical evoked potentials. Lect Notes in Bioinform 4146, pp. 174-183.

Smolinski T.G., Buchanan R., Boratyn G.M., Milanova M., Prinz A.A. (2006). Independent component analysis-motivated approach to classificatory decomposition of cortical evoked potentials. BMC Bioinformatics 7: Art. No. S8 Suppl. 2.

Langton J.T., Prinz A.A., Hickey T.J. (2006). Combining pixelization and dimensional stacking. Lect Notes in Comp Sci 4292(2): 617-626. (bibtex)

Smolinski T.G., Soto-Treviño C., Rabbah P., Nadim F., Prinz A.A. (2006). Analysis of Biological Neurons via Modeling and Rule Mining. Int J IT&IC, 1(2): 293-302.

Smolinski T.G., Milanova M., Boratyn G.M., Buchanan R., Prinz A.A. (2006). Multi-objective evolutionary algorithms and rough sets for decomposition and analysis of cortical evoked potentials,” In: Proc. of the IEEE International Conference on Granular Computing (GrC 2006); Atlanta, Georgia, May 2006, pp. 635-638.

Taylor A.L., Hickey T.J., Prinz A.A., Marder E. (2006). Structure and visualization of high-dimensional conductance spaces. J Neurophysiol 96: 891-905.

Dong M., Sun X., Prinz A.A., Wang H-S (2006). Effect of simulated I_to on guinea pig and canine ventricular action potential morphology. Am J Physiol Heart Circ Physiol doi: 10.1152/ajpheart.00084.2006.

Thirumalai V., Prinz A.A., Johnson C.D., Marder E. (2005). Red pigment concentrating hormone strongly enhances the strength of the feedback to the pyloric rhythm oscillator but has little effect on pyloric rhythm period. J Neurophysiol 95(3): 1762-1770.

Bucher D., Prinz A.A., Marder E. (2005). Animal-to-animal variability in motor pattern production in adults and during growth. J Neurosci 25:1611-1619.
Rated “must read” by the Faculty of 1000.

Prinz A.A., Bucher D., Marder E. (2004). Similar network activity from disparate circuit parameters. Nature Neurosci 7:1345-1352.
Rated “must read” by the Faculty of 1000.

Oprisan S.A., Prinz A.A., Canavier C.C. (2004). Phase resetting and phase locking in hybrid circuits of one model and one biological neuron. Biophys J 87: 2283-2298.

Prinz A.A., Billimoria C.P., Marder E. (2003). Alternative to hand-tuning conductance-based models: construction and analysis of databases of model neurons. J Neurophysiol 90: 3998-4015.
Rated “exceptional” by the Faculty of 1000.
Full text linked from here.
Database is described here and is available upon request.

Prinz A.A., Thirumalai V., Marder E. (2003). The functional consequences of changes in the strength and duration of synaptic inputs to oscillatory neurons. J Neurosci 23: 943-954.
Rated “must read” by the Faculty of 1000.
Free pdf.

Prinz A.A., Fromherz P. (2003). Effect of neuritic cables on conductance estimates for remote electrical synapses. J Neurophysiol 89: 2215-2224.

Kupper J., Prinz A.A., Fromherz P. (2002). Recombinant Kv1.3 potassium channels stabilize tonic firing of cultured rat hippocampal neurons. Eur J Physiol 443: 541-547.

Prinz A.A., Fromherz P. (2000). Electrical synapses by guided growth of cultured neurons from the snail Lymnaea stagnalis. Biol Cybern 82(4): L1-L5.

Reviews

Hudson AE, Archila S, Prinz AA (2010). Identifiable cells in the stomatogastric ganglion. Physiology 25(5): 311-318.

Prinz AA (2010). Computational approaches to neuronal network analysis. Philos T R Soc B 365(1551): 2397-2405.

Prinz A.A. (2006). Insights from models of rhythmic motor systems. Curr Opin Neurobiol 16(6): 615-620.

Prinz A.A. (2004). The dynamic clamp a decade after its invention. AxoBits 40: 6-7.
Free pdf.

Prinz A.A., Abbott L.F., Marder E. (2004). The dynamic clamp comes of age. TINS 27: 218-224.

Marder E., Prinz A.A. (2002). Modeling stability in neuron and network function: the role of activity in homeostasis. BioEssays 24: 1145-1154.
Free pdf.

Book chapters

Hooper R, Prinz AA (in press). Biohybrid Circuits: The Dynamic Clamp. In: Jung R, ed. Biohybrid Systems. Wiley-VCH, Weinheim, Germany.

Prinz AA, Smolinski TG, Hudson AE (2011). Understanding Animal-to-Animal Variability in Neuronal and Network Properties. In: Ding M, Glanzman D, eds. Neuronal Variability and its Functional Significance. Oxford University Press, Oxford, UK: 119-138.

Achuthan S, Sieling FH, Prinz AA, Canavier CC (2011). Phase Resetting in the Presence of Noise and Heterogeneity. In: Ding M, Glanzman D, eds. Neuronal Variability and its Functional Significance. Oxford University Press, Oxford, UK: 104-118.

National Research Council: Committee on Forefronts of Science at the Interface of Physical and Life Sciences (2010). Research at the Intersection of the Physical and Life Sciences. The National Academies Press, Washington, DC.

Calabrese R.L., Prinz A.A. (2009). Realistic modeling of small neuronal networks. In: De Schutter E, ed. Computational Modeling Methods for Neuroscientists. MIT Press.

Canavier C.C., Sieling F.H., Prinz A.A. (in press). Dynamic-clamp constructed hybrid circuits for the study of synchronization phenomena in networks of bursting neurons. In: Destexhe A., Bal T., eds. Dynamic clamp: from principles to applications. Springer.

Prinz A.A. (2008). Plasticity and stability in neuronal and network dynamics. In: Soltesz I., Staley K., eds. Computational Neuroscience in Epilepsy. Elsevier.

Prinz A.A. (2007). Computational exploration of neuron and neural network models in neurobiology. In: Crasto C.J., ed. Methods in Molecular Biology: Bioinformatics. Humana Press, Totowa NJ: 167-179.

Smolinski T.G., Prinz A.A., Zurada J.M. (2007). Hybridization of Rough Sets and Multi-Objective Evolutionary Algorithms for Classificatory Signal Decomposition. In: Hassanien A.-E., Suraj Z., Slezak D., Lingras P., eds. Rough Computing: Theories, Technologies, and Applications. Information Science Reference, Hershey NY: 204-227.

Abbott L.F., Thoroughman K., Prinz A., Thirumalai V., Marder E. (2003). Activity-dependent modification of intrinsic and synaptic conductances in neurons and rhythmic networks. In: Van Ooyen A., ed. Modeling Neural Development. MIT Press, Cambridge MA: 151-166.

Commentaries

Prinz A.A. (2008). Understanding epilepsy through network modeling. Proc Natl Acad Sci USA 105(16): 5953-5954.

Prinz A.A. (2004). Neural networks: models and neurons show hybrid vigor in real time. Curr Biol 14: R661-R662.

Marder E., Prinz A.A. (2003). Current compensation in neuronal homeostasis. Neuron 37 (1): 2-4.

Encyclopedia Contributions

Marder E, Prinz AA, Abbott LF (2003). Dynamic clamp: modeling with biological neurons. In: Adelman G, Smith BH, eds. Encyclopedia of Neuroscience, 3rd ed. Elsevier.

Prinz AA (2007). Neuronal Parameter Optimization. Scholarpedia: 6503.

Cudmore RH, Prinz AA (submitted). Dynamic Clamp. Scholarpedia.

Peer-Reviewed Conference Contributions

Smolinski TG, Prinz AA (2010). Classifying functional and non-functional model neurons using the theory of rough sets. BMC Neuroscience 11(Suppl 1): P157.

Gunay C, Dharmar L, Sieling F, Marley R, Lin WH, Baines RA, Prinz AA (2010). Modeling Drosophila motoneurons to examine the functional effect of Na channel splice variants. BMC Neuroscience 11(Suppl 1): P147.

Soofi W, Prinz AA (2010). Covarying ionic conductances to emulate phase maintenance in stomatogastric neurons. BMC Neuroscience 11(Suppl 1): P60.

Olypher AV, Lytton WW, Prinz AA (2010). Transformation of inputs in a model of the rat hippocampal CA1 network. BMC Neuroscience 11(Suppl 1): P56.

Sieling FH, Simmers J, Prinz AA, Nargeot R (2010). Changes in electrical coupling via dynamic clamp produces correlates of operant conditioning in the feeding CPG networks of Aplysia. BMC Neuroscience 11(Suppl 1): P1.

Smolinski TG, Prinz AA (2010). Rough Sets for Solving Classification Problems in Computational Neuroscience. Rough Sets and Current Trends in Computing, Proceedings 6086: 620-629.

Sieling FH, Canavier CC, Prinz AA (2009). Inclusion of noise in iterated firing maps based on the PRC. BMC Neuroscience 10(Suppl. 1): P345.

Hudson AE, Prinz AA (2009). Activity-dependent conductance relationships in a model neuron database. BMC Neuroscience 10(Suppl. 1): P41.

Prinz AA, Olypher AV (2009). Geometry and dynamics of activity-dependent homeostatic regulation in neurons. BMC Neuroscience 10(Suppl. 1): P203.

Smolinski TG, Prinz AA (2009). Multi-objective evolutionary algorithms for model parameter value selection matching biological behavior under different simulation scenarios. BMC Neuroscience 10(Suppl. 1): P260.

Gunay C, Prinz AA (2009). Calcium sensor parameters and readout configurations for activity-dependent homeostatic regulation of pyloric network rhythms in the lobster stomatogastric ganglion. BMC Neuroscience 10(Suppl. 1): O4.

Smolinski TG, Prinz AA (2009). Computational Intelligence in Modeling of Biological Neurons: A Case Study of an Invertebrate Pacemaker Neuron. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, GA, June 14-19, 2009, 2964-2970.

Gunay C, Prinz AA (2009). Finding sensors for homeostasis of biological neuronal networks using artificial neural networks. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, GA, June 14-19, 2009.

Gurel Kazanci F, Maran SK, Prinz AA, Canavier CC (2008). Predicting n:1 locking in pulse coupled two-neuron networks using phase resetting theory. BMC Neuroscience 9(Suppl. 1): 136.

Maran SK, Sieling FH, Prinz AA, Canavier CC (2008). Predicting excitatory phase resetting curves in bursting neurons. BMC Neuroscience 9(Suppl. 1): 134.

Sieling FH, Canavier CC, Prinz AA (2008). Predicting phase-locking in excitatory hybrid circuits. BMC Neuroscience 9(Suppl. 1): 133.

Smolinski TG, Soto-Trevino C, Rabbah P, Nadim F, Prinz AA (2008). Systematic selection of model parameter values matching biological behavior under different simulation scenarios. BMC Neuroscience 9(Suppl. 1): 53.

Gunay C, Hooper RM, Hammett KR, Prinz AA (2008). Calcium sensor properties for activity-dependent homeostatic regulation of pyloric network rhythms in the lobster stomatogastric ganglion. BMC Neuroscience 9(Suppl. 1): 42.

Langton JT, Prinz AA, Hickey TJ (2007). Neurovis: combining dimensional stacking and pixelization to visually explore, analyze, and mine multidimensional multivariate data. In: Proceedings of SPIE: Visualization and Data Analysis 6495: 64950H1-64950H12, SPIE and IS&T.

Vargas, Prinz AA (2007). Does reliable neuromodulation require that neuronal network parameters are tightly regulated? BMC Neuroscience 8(Suppl. 2): 195.

Smolinski TG, Soto-Trevino C, Rabbah P, Nadim F, Prinz AA (2007). Systematic computational exploration of the parameter space of the multi-compartment model of the lobster pyloric pacemaker kernel suggests that the kernel can achieve functional activity under various parameter configurations. BMC Neuroscience 8(Suppl. 2): 164.

Langton JT, Prinz AA, Wittenberg DK, Hickey TJ (2006). Leveraging layout with dimensional stacking and pixelization to facilitate feature discovery and directed queries. Lecture Notes in Comput Sci 4370: 77-91.

Smolinski TG, Boratyn GM, Milanova M, Buchanan R, Prinz AA (2006). Hybridization of independent component analysis, rough sets, and multi-objective evolutionary algorithms for classificatory decomposition of cortical evoked potentials. Lect Notes in Bioinform 4146: 174-183.

Smolinski TG, Buchanan R, Boratyn GM, Milanova M, Prinz AA (2006). Independent component analysis-motivated approach to classificatory decomposition of cortical evoked potentials. BMC Bioinformatics 7: Art. No. S8 Suppl. 2.

Langton JT, Prinz AA, Hickey TJ (2006). Combining pixelization and dimensional stacking. Lecture Notes in Comput Sci 4292: 617–626.

Smolinski TG, Soto-Trevino C, Rabbah P, Nadim F, Prinz AA (2006). Analysis of biological neurons via modeling and rule mining. Int J IT & IC 1(2): 293-302.

Smolinski TG, Milanova M, Boratyn GM, Buchanan R, Prinz AA (2006). Multi-objective evolutionary algorithms and rough sets for decomposition and analysis of cortical evoked potentials. Proceedings of the IEEE International Conference on Granular Computing (GrC 2006), Atlanta, GA, May 10-12, 2006, pp. 635 - 638.

Hong E., Taylor A.L., Prinz A.A. (2006). Comparison of fast and slow tonically spiking neurons based on conductance space exploration of model neurons from two different phyla. Computational Neuroscience Meeting, July 16-20, 2006, Edinburgh, Scotland.

Conference Abstracts

Langton J.T., Prinz A.A., Hickey T.J. (2006). NeuroVis: Exploring interaction techniques by combining dimensional stacking and pixelization to visualize multidimensional multivariate data. InfoVis 2006.

Buchanan R., Milanova M., Smolinski T.G., Boratyn G.M., Prinz A.A. (2006). Decomposition and analysis of cortical evoked potentials using ICA. 3rd Annual MidSouth Computational Biology and Bioinformatics Society Conference (MCBIOS 2006), Baton Rouge, Louisiana, February 2-4, 2006.

Smolinski T.G., Prinz A.A., Soto-Treviño C., Rabbah P., Nadim F. (2005). Computational exploration of a multi-compartment model of the lobster pyloric pacemaker kernel. Society for Neuroscience 35th Annual Meeting, Washington, D.C., November 12-16, 2005.

Smolinski T.G., Soto-Treviño C., Rabbah P., Nadim F., Prinz A.A. (2005). Application of evolutionary algorithms-based pseudo-association rule mining to analysis of the intrinsic properties of the PD neuron in the lobster pyloric network. Second SECABC Fall Workshop on Biocomputing; Atlanta, Georgia, October 27, 2005.