Physical Review D / Jan 01, 1994

Roberts, C. D., Cahill, R. T., Sevior, M. E., & Iannella, N. (1994). <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>π</mml:mi><mml:mo>−</mml:mo><mml:mi>π</mml:mi></mml:math>scattering in a QCD-based model field theory. Physical Review D, 49(1), 125–137. https://doi.org/10.1103/physrevd.49.125

Proceedings of the IEEE / May 01, 2014

Rahimi Azghadi, M., Iannella, N., Al-Sarawi, S. F., Indiveri, G., & Abbott, D. (2014). Spike-Based Synaptic Plasticity in Silicon: Design, Implementation, Application, and Challenges. Proceedings of the IEEE, 102(5), 717–737. https://doi.org/10.1109/jproc.2014.2314454

Neural Networks / Jul 01, 2001

Iannella, N., & Back, A. D. (2001). A spiking neural network architecture for nonlinear function approximation. Neural Networks, 14(6–7), 933–939. https://doi.org/10.1016/s0893-6080(01)00080-6

Neural Networks / Sep 01, 2013

Rahimi Azghadi, M., Al-Sarawi, S., Abbott, D., & Iannella, N. (2013). A neuromorphic VLSI design for spike timing and rate based synaptic plasticity. Neural Networks, 45, 70–82. https://doi.org/10.1016/j.neunet.2013.03.003

Information Processing Letters / Sep 01, 2005

Iannella, N., & Kindermann, L. (2005). Finding iterative roots with a spiking neural network. Information Processing Letters, 95(6), 545–551. https://doi.org/10.1016/j.ipl.2005.05.022

eLife / Jul 30, 2020

Mäki-Marttunen, T., Iannella, N., Edwards, A. G., Einevoll, G. T., & Blackwell, K. T. (2020). A unified computational model for cortical post-synaptic plasticity. ELife, 9. CLOCKSS. https://doi.org/10.7554/elife.55714

PLoS ONE / Dec 31, 2012

Chappell, J. M., Iqbal, A., Iannella, N., & Abbott, D. (2012). Revisiting Special Relativity: A Natural Algebraic Alternative to Minkowski Spacetime. PLoS ONE, 7(12), e51756. https://doi.org/10.1371/journal.pone.0051756

PLoS ONE / Feb 13, 2014

Rahimi Azghadi, M., Iannella, N., Al-Sarawi, S., & Abbott, D. (2014). Tunable Low Energy, Compact and High Performance Neuromorphic Circuit for Spike-Based Synaptic Plasticity. PLoS ONE, 9(2), e88326. https://doi.org/10.1371/journal.pone.0088326

International Journal of Neural Systems / Jul 18, 2018

Eshraghian, J. K., Baek, S., Kim, J.-H., Iannella, N., Cho, K., Goo, Y. S., Iu, H. H. C., Kang, S.-M., & Eshraghian, K. (2018). Formulation and Implementation of Nonlinear Integral Equations to Model Neural Dynamics Within the Vertebrate Retina. International Journal of Neural Systems, 28(07), 1850004. https://doi.org/10.1142/s0129065718500041

IEEE Transactions on Circuits and Systems II: Express Briefs / Dec 01, 2017

Eshraghian, J. K., Cho, K.-R., Iu, H. H. C., Fernando, T., Iannella, N., Kang, S.-M., & Eshraghian, K. (2017). Maximization of Crossbar Array Memory Using Fundamental Memristor Theory. IEEE Transactions on Circuits and Systems II: Express Briefs, 64(12), 1402–1406. https://doi.org/10.1109/tcsii.2017.2767078

IEEE Sensors Journal / Aug 01, 2016

Cho, K., Baek, S., Cho, S.-W., Kim, J.-H., Goo, Y. S., Eshraghian, J. K., Iannella, N., & Eshraghian, K. (2016). Signal Flow Platform for Mapping and Simulation of Vertebrate Retina for Sensor Systems. IEEE Sensors Journal, 16(15), 5856–5866. https://doi.org/10.1109/jsen.2016.2561310

Network: Computation in Neural Systems / Mar 11, 2015

McDonnell, M. D., Iannella, N., To, M.-S., Tuckwell, H. C., Jost, J., Gutkin, B. S., & Ward, L. M. (2015). A review of methods for identifying stochastic resonance in simulations of single neuron models. Network: Computation in Neural Systems, 26(2), 35–71. https://doi.org/10.3109/0954898x.2014.990064

2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing / Dec 01, 2011

Kavehei, O., Al-Sarawi, S., Cho, K.-R., Iannella, N., Kim, S.-J., Eshraghian, K., & Abbott, D. (2011, December). Memristor-based synaptic networks and logical operations using in-situ computing. 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing. https://doi.org/10.1109/issnip.2011.6146610

The 2012 International Joint Conference on Neural Networks (IJCNN) / Jun 01, 2012

Azghadi, M. R., Al-Sarawi, S., Iannella, N., & Abbott, D. (2012, June). Efficient design of triplet based Spike-Timing Dependent Plasticity. The 2012 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn.2012.6252820

BMC Neuroscience / Dec 01, 2020

29th Annual Computational Neuroscience Meeting: CNS*2020. (2020). BMC Neuroscience, 21(S1). https://doi.org/10.1186/s12868-020-00593-1

2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing / Dec 01, 2011

Azghadi, M. R., Kavehei, O., Al-Sarawi, S., Iannella, N., & Abbott, D. (2011, December). Novel VLSI implementation for triplet-based spike-timing dependent plasticity. 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing. https://doi.org/10.1109/issnip.2011.6146525

The 2012 International Joint Conference on Neural Networks (IJCNN) / Jun 01, 2012

Rahimi Azghadi, M., Al-Sarawi, S., Iannella, N., & Abbott, D. (2012, June). Design and implementation of BCM rule based on spike-timing dependent plasticity. The 2012 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn.2012.6252778

Journal of Neurophysiology / Nov 01, 2018

Moezzi, B., Schaworonkow, N., Plogmacher, L., Goldsworthy, M. R., Hordacre, B., McDonnell, M. D., Iannella, N., Ridding, M. C., & Triesch, J. (2018). Simulation of electromyographic recordings following transcranial magnetic stimulation. Journal of Neurophysiology, 120(5), 2532–2541. https://doi.org/10.1152/jn.00626.2017

2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) / Oct 01, 2016

Eshraghian, J. K., Baek, S., Cho, K., Iannella, N., Kim, J.-H., Goo, Y. S., Iu, H. H. C., Fernando, T., & Eshraghian, K. (2016, October). Modelling and analysis of signal flow platform implementation into retinal cell pathway. 2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS). https://doi.org/10.1109/apccas.2016.7804011

Journal of Computational Neuroscience / Aug 02, 2016

Moezzi, B., Iannella, N., & McDonnell, M. D. (2016). Ion channel noise can explain firing correlation in auditory nerves. Journal of Computational Neuroscience, 41(2), 193–206. https://doi.org/10.1007/s10827-016-0613-9

Journal of Integrative Neuroscience / Jun 01, 2006

IANNELLA, N., & TANAKA, S. (2006). ANALYTICAL SOLUTIONS FOR NONLINEAR CABLE EQUATIONS WITH CALCIUM DYNAMICS I: DERIVATIONS. Journal of Integrative Neuroscience, 05(02), 249–272. https://doi.org/10.1142/s0219635206001124

Frontiers in Physics / Nov 17, 2016

Chappell, J. M., Hartnett, J. G., Iannella, N., Iqbal, A., & Abbott, D. (2016). Time As a Geometric Property of Space. Frontiers in Physics, 4. https://doi.org/10.3389/fphy.2016.00044

2013 IFIP/IEEE 21st International Conference on Very Large Scale Integration (VLSI-SoC) / Oct 01, 2013

Azghadi, M. R., Al-Sarawi, S., Iannella, N., & Abbott, D. (2013, October). A new compact analog VLSI model for Spike Timing Dependent Plasticity. 2013 IFIP/IEEE 21st International Conference on Very Large Scale Integration (VLSI-SoC). https://doi.org/10.1109/vlsi-soc.2013.6673236

Current Bioinformatics / Jun 28, 2019

Wong, K. K. L. (2019). Optimization in the Design of Natural Structures, Biomaterials, Bioinformatics and Biometric Techniques for Solving Physiological Needs and Ultimate Performance of Bio-devices. Current Bioinformatics, 14(5), 374–375. https://doi.org/10.2174/157489361405190628122355

BMC Neuroscience / Oct 01, 2018

27th Annual Computational Neuroscience Meeting (CNS*2018): Part One. (2018). BMC Neuroscience, 19(S2). https://doi.org/10.1186/s12868-018-0452-x

Journal of Integrative Neuroscience / Jun 01, 2007

IANNELLA, N., & TANAKA, S. (2007). ANALYTICAL SOLUTIONS FOR NONLINEAR CABLE EQUATIONS WITH CALCIUM DYNAMICS II: SALTATORY TRANSMISSION IN A SPARSELY EXCITABLE CABLE MODEL. Journal of Integrative Neuroscience, 06(02), 241–277. https://doi.org/10.1142/s0219635207001489

Frontiers in Computational Neuroscience / Jun 09, 2017

Iannella, N., & Launey, T. (2017). Modulating STDP Balance Impacts the Dendritic Mosaic. Frontiers in Computational Neuroscience, 11. https://doi.org/10.3389/fncom.2017.00042

2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS) / Dec 01, 2013

Azghadi, M. R., Al-Sarawi, S., Abbott, D., & Iannella, N. (2013, December). Pairing frequency experiments in visual cortex reproduced in a neuromorphic STDP circuit. 2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS). https://doi.org/10.1109/icecs.2013.6815396

1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings. ANZIIS 96

Iannella, N., & Bouzerdoum, A. (n.d.). Time evolution of receptive fields. 1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings. ANZIIS 96. https://doi.org/10.1109/anziis.1996.573907

2017 International Joint Conference on Neural Networks (IJCNN) / May 01, 2017

Iannella, N., & Launey, T. (2017, May). Synaptic efficacy mosaics and the impact of morphology. 2017 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn.2017.7966335

2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) / Oct 01, 2016

Baek, S., Eshraghian, J. K., Cho, K., Iannella, N., Kim, J.-H., Iu, H. H. C., Fernando, T., & Eshraghian, K. (2016, October). Live demonstration: Signal flow platform implementation into retinal cell pathway. 2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS). https://doi.org/10.1109/apccas.2016.7804033

2014 16th International Conference on Harmonics and Quality of Power (ICHQP) / May 01, 2014

Shahabi, N., Zivanovic, R., Iannella, N., & Al-Sarawi, S. (2014, May). Global sensitivity and uncertainty analysis of Transients in the Universal Line Model. 2014 16th International Conference on Harmonics and Quality of Power (ICHQP). https://doi.org/10.1109/ichqp.2014.6842920

Journal of Multiscale Neuroscience / Jul 25, 2023

Iannella, N., & Poznanski, R. R. (2023). Approximate analytical solution of a (V,m,h) reduced system for backpropagating action potentials in sparsely excitable dendrites. Journal of Multiscale Neuroscience, 2(2), 350–374. https://doi.org/10.56280/1583164092

Journal of Physics Communications / Jun 01, 2023

Chappell, J. M., Hartnett, J. G., Iannella, N., Iqbal, A., Berkahn, D. L., & Abbott, D. (2023). A new derivation of the Minkowski metric. Journal of Physics Communications, 7(6), 065001. https://doi.org/10.1088/2399-6528/acd986

Jan 28, 2020

Mäki-Marttunen, T., Iannella, N., Edwards, A. G., Einevoll, G. T., & Blackwell, K. T. (2020). A unified computational model for cortical post-synaptic plasticity. https://doi.org/10.1101/2020.01.27.921254

Brain Informatics and Health / Jan 01, 2020

Iannella, N., & Condemine, M. (2020). Neurons and Plasticity: What Do Glial Cells Have to Do with This? In Functional Brain Mapping: Methods and Aims (pp. 13–46). Springer Singapore. https://doi.org/10.1007/978-981-15-6883-1_2

BMC Neuroscience / Aug 01, 2016

Sharpee, T. O., Destexhe, A., Kawato, M., Sekulić, V., Skinner, F. K., Wójcik, D. K., Chintaluri, C., Cserpán, D., Somogyvári, Z., Kim, J. K., Kilpatrick, Z. P., Bennett, M. R., Josić, K., Elices, I., Arroyo, D., Levi, R., Rodriguez, F. B., Varona, P., … Chhabria, K. (2016). 25th Annual Computational Neuroscience Meeting: CNS-2016. BMC Neuroscience, 17(S1). https://doi.org/10.1186/s12868-016-0283-6

PLoS ONE / Aug 22, 2014

Iannella, N., Launey, T., Abbott, D., & Tanaka, S. (2014). A Nonlinear Cable Framework for Bidirectional Synaptic Plasticity. PLoS ONE, 9(8), e102601. https://doi.org/10.1371/journal.pone.0102601

Frontiers in Computational Neuroscience / Dec 23, 2014

Moezzi, B., Iannella, N., & McDonnell, M. D. (2014). Modeling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics. Frontiers in Computational Neuroscience, 8. https://doi.org/10.3389/fncom.2014.00163

PLoS ONE / Dec 08, 2014

McDonnell, M. D., Yaveroğlu, Ö. N., Schmerl, B. A., Iannella, N., & Ward, L. M. (2014). Motif-Role-Fingerprints: The Building-Blocks of Motifs, Clustering-Coefficients and Transitivities in Directed Networks. PLoS ONE, 9(12), e114503. https://doi.org/10.1371/journal.pone.0114503

Frontiers in Computational Neuroscience / Jan 01, 2010

Iannella. (2010). Spike timing-dependent plasticity as the origin of the formation of clustered synaptic efficacy engrams. Frontiers in Computational Neuroscience. https://doi.org/10.3389/fncom.2010.00021

Neuroscience Letters / Jul 01, 2006

Iannella, N., & Tanaka, S. (2006). Synaptic efficacy cluster formation across the dendrite via STDP. Neuroscience Letters, 403(1–2), 24–29. https://doi.org/10.1016/j.neulet.2006.03.079

Mathematical Biosciences / Mar 01, 2004

Iannella, N., Tuckwell, H. C., & Tanaka, S. (2004). Firing properties of a stochastic PDE model of a rat sensory cortex layer 2/3 pyramidal cell. Mathematical Biosciences, 188(1–2), 117–132. https://doi.org/10.1016/j.mbs.2003.10.002

The Neural Basis of Early Vision / Jan 01, 2003

Iannella, N., Ribot, J., & Tanaka, S. (2003). Long-Range Horizontal Connections Assist the Formation of Robust Orientation Maps. In The Neural Basis of Early Vision (pp. 221–224). Springer Japan. https://doi.org/10.1007/978-4-431-68447-3_75

BMC Neuroscience / Oct 01, 2018

27th Annual Computational Neuroscience Meeting (CNS*2018): Part Two. (2018). BMC Neuroscience, 19(S2). https://doi.org/10.1186/s12868-018-0451-y