A. A. Lazar. Time Encoding with an Integrate-and-Fire Neuron with a Refractory Period. The Computational Neuroscience Meeting, July 2003. A. A. Lazar. Information Representation with an Ensemble of Hodgkin-Huxley Neurons. Neurocomputing, volume 70, pages 1764-1771, June 2007. A. A. Lazar. The Hodgkin-Huxley Neuron as a Neuro-Modulator. Computational and Systems Neuroscience Meeting, March 2005. A. A. Lazar. Time Encoding with Filter Banks and Integrate-and-Fire Neurons. The Computational Neuroscience Meeting, July 2004. A. J. Kim and A. A. Lazar. Recovery of Stimuli Encoded with a Hodgkin-Huxley Neuron Using Conditional PRCs. Phase Response Curves in Neuroscience, Springer, volume 6, pages 257-277, 2012. A. A. Lazar. Time Encoding with an Integrate-and-Fire Neuron with a Refractory Period. Neurocomputing, volume 58-60, pages 53-58, June 2004. A. A. Lazar. Time Encoding Using Filter Banks and Integrate and-Fire Neurons. BNET Technical Report #2-03, September 2003. A. A. Lazar. A Simple Model of Spike Processing. BNET Technical Report #2-05, April 2005. L. E. Givon and A. A. Lazar. An Open Architecture for the Massively Parallel Emulation of the Drosophila Brain on Multiple GPUs. Computational Neuroscience Meeting, July 2012. A. A. Lazar. Modeling the Architecture of the Olfactory System. BNET Technical Report #3-05, May 2005. A. A. Lazar. Population Encoding with Hodgkin-Huxley Neurons. IEEE Transactions on Information Theory, volume 56, issue 2, pages 821-837, February 2010. A. A. Lazar. Information Representation with an Ensemble of Hodgkin-Huxley Neurons. Computational Neuroscience Meeting, July 2006. A. A. Lazar. Time Encoding with the Integrate-and-Fire Neuron. Neural Information and Coding Workshop, March 2003. A. J. Kim and A. A. Lazar. Recovery of Stimuli Encoded with a Hodgkin-Huxley Neuron Using Conditional PRCs. Computational Neuroscience Meeting, July 2009. A. A. Lazar. Recovery of Stimuli Encoded with Hodgkin-Huxley Neurons. Computational and Systems Neuroscience Meeting, February 2007. A. A. Lazar. Recovery of Stimuli Encoded with Spiking Neuron Models. Conference on Engineering Principles in Biological Systems, December 2006. A. A. Lazar. Spatio-Temporal Models for Time Encoding and Stimulus Recovery. Computational and Systems Neuroscience Meeting, March 2004. A. A. Lazar. A Simple Model of Spike Processing. Neurocomputing, volume 69, pages 1081-1085, June 2006. A. A. Lazar. A Simple Model of Spike Processing. Computational Neuroscience Meeting, July 2005. A. A. Lazar. Neural Diversity and Ensemble Encoding. Computational and Systems Neuroscience Meeting, March 2006. L. E. Givon and A. A. Lazar. Neurokernel: An Open Architecture for the Massively Parallel Emulation of Drosophila Brain Models on Multiple GPUs. Workshop on Insect Vision: Cells, Computation, and Behavior, March 2013. A. A. Lazar. Time Encoding Machines with Multiplicative Coupling, Feedforward and Feedback. IEEE Transactions on Circuits and Systems-II: Express Briefs, volume 53, issue 8, pages 672-676, August 2006. A. A. Lazar. Time Encoding Machines. Neuromorphic Engineering Workshop, July 2007. A. A. Lazar. The t-Transform and its Inverse in Neural Encoding and Decoding. Workshop on Neural Coding: Beyond Shannon, July 2013. N. H. Ukani, A. Tomkins, C.-H. Yeh, W. Bruning, A. L. Fenichel, Y. Zhou, Y.-C. Huang, D. Florescu, C. L. Ortiz, P. Richmond, C.-C. Lo, D. Coca, A.-S. Chiang, and A. A. Lazar. NeuroNLP: a Natural Language Portal for Aggregated Fruit Fly Brain Data. Neurokernel Request for Comments, Neurokernel RFC #8, December 2016. L. E. Givon and A. A. Lazar. Neurokernel: An Open Scalable Software Framework for Emulation and Validation of Drosophila Brain Models on Multiple GPUs. Neurokernel Request for Comments, Neurokernel RFC #1, February 2014. L. E. Givon and A. A. Lazar. Generating an Executable Model of the Drosophila Central Complex. Neurokernel Request for Comments, Neurokernel RFC #6, May 2016. N. H. Ukani, C.-H. Yeh, A. Tomkins, Y. Zhou, D. Florescu, C. L. Ortiz, Y.-C. Huang, C.-T. Wang, P. Richmond, C.-C. Lo, D. Coca, A.-S. Chiang, and A. A. Lazar. The Fruit Fly Brain Observatory: from Structure to Function. Computational and Systems Neuroscience Meeting, February 2017. Y. Zhou, K. Psychas, N. H. Ukani, and A. A. Lazar. Visualizing Parallel Information Processing in the Fruit Fly Retina. Computational and Systems Neuroscience Meeting, February 2016. L. E. Givon and A. A. Lazar. Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain. PLOS ONE, volume 11, e0146581, January 2016. N. H. Ukani, C.-H. Yeh, A. Tomkins, Y. Zhou, D. Florescu, C. L. Ortiz, Y.-C. Huang, C.-T. Wang, M. K. Turkcan, T. Liu, P. Richmond, C.-C. Lo, D. Coca, A.-S. Chiang, and A. A. Lazar. The Fruit Fly Brain Observatory: From Structure to Function. bioRxiv, volume 580290, March 2019. L. E. Givon and A. A. Lazar. Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain. Neurokernel Request for Comments, Neurokernel RFC #4, October 2015. N. H. Ukani, C.-H. Yeh, A. Tomkins, Y. Zhou, M. K. Turkcan, T. Liu, J. Marty, D. Florescu, C. L. Ortiz, Y.-C. Huang, C.-T. Wang, P. Richmond, C.-C. Lo, D. Coca, A.-S. Chiang, and A. A. Lazar. Fruit Fly Brain Observatory Source Code, Installation and Launching. Github, October 2018. M. K. Turkcan, T. Liu, C.-H. Yeh, Y. Zhou, and A. A. Lazar. FlyBrainLab: An Interactive Computing Environment for the Fruit Fly Brain. Society of Neuroscience, October 2019. N. H. Ukani, C.-H. Yeh, A. Tomkins, Y. Zhou, D. Florescu, C. L. Ortiz, Y.-C. Huang, C.-T. Wang, P. Richmond, C.-C. Lo, D. Coca, A.-S. Chiang, and A. A. Lazar. The Fruit Fly Brain Observatory: from Structure to Function. Neurokernel Request for Comments, Neurokernel RFC #7, December 2016. N. H. Ukani, A. Tomkins, C.-H. Yeh, W. Bruning, A. L. Fenichel, Y. Zhou, Y.-C. Huang, D. Florescu, C. L. Ortiz, P. Richmond, C.-C. Lo, D. Coca, A.-S. Chiang, and A. A. Lazar. NeuroNLP: A Natural Language Portal for Aggregated Fruit Fly Brain Data. Computational Neuroscience Meeting, BMC Neuroscience 2017, volume 18 (Suppl 1):60, July 2017. T. Liu, C.-H. Yeh, and A. A. Lazar. Time-Dependent Simultaneous Configural and Elemental Odorant Mixture Processing. COSYNE*2020, February 2020. C.-H. Yeh, Y. Zhou, N. H. Ukani, and A. A. Lazar. NeuroGFX: a Graphical Functional Explorer for Fruit Fly Brain Circuits. Neurokernel Request for Comments, Neurokernel RFC #9, December 2016. M. K. Turkcan, Y. Zhou, and A. A. Lazar. A Circuit Library for Exploring the Functional Logic of Massive Feedback Loops in Drosophila Brain. COSYNE 2022, 2022. A. A. Lazar and C.-H. Yeh. An Open-Source Model of the Early Olfactory System of the Fruit Fly and Its I/O Characterization. Society for Neuroscience Abstracts, November 2017. A. A. Lazar and C.-H. Yeh. Functional Identification of an Antennal Lobe DM4 Projection Neuron of the Fruit Fly. Computational Neuroscience Meeting, volume 15, July 2014. A. A. Lazar and C.-H. Yeh. A Molecular Odorant Transduction Model and the Complexity of Spatio-Temporal Encoding in the Drosophila Antenna. PLOS Computational Biology, volume 16, issue 4, April 2020. A. A. Lazar and C.-H. Yeh. Predictive Coding in the Drosophila Antennal Lobe. BMC Neuroscience 2019, 20 (Suppl 1): P346, 28th Annual Computational Neuroscience Meeting, 2019. A. A. Lazar and C.-H. Yeh. A Parallel Processing Model of Drosophila Olfactory Sensory Neurons and Its Biological Validation. bioRxiv (available at https://www.biorxiv.org/content/10.1101/237669v1), December 2017. A. A. Lazar and C.-H. Yeh. A Molecular Odorant Transduction Model and Combinatorial Encoding in the Drosophila Antennae. BMC Neuroscience 2018, 19(Suppl 2):F3, 27th Computational Neuroscience Meeting (featured oral presentation), 2018. A. A. Lazar and C.-H. Yeh. A Molecular Odorant Transduction Model and the Complexity of Combinatorial Encoding in the Drosophila Antenna. bioRxiv (the first version, published on bioRxiv in December 2017, is available at https://www.biorxiv.org/content/10.1101/237669v1), volume 647107, May 2019. A. A. Lazar and E. A. Pnevmatikakis. Encoding, Processing and Decoding of Sensory Stimuli with a Spiking Neural Population. AREADNE 2008, Research in Encoding and Decoding of Neural Ensembles, June 2008. A. A. Lazar and E. A. Pnevmatikakis. Faithful Representation of Stimuli with a Population of Integrate-and-Fire Neurons. Neural Computation, The MIT Press, volume 20, issue 11, pages 2715-2744, November 2008. A. A. Lazar and E. A. Pnevmatikakis. Invariant Representations of Visual Streams in the Spike Domain. Bernstein Conference in Computational Neuroscience, September 2009. A. A. Lazar and E. A. Pnevmatikakis. Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds. EURASIP Journal on Advances in Signal Processing, volume 2009, 2009. A. A. Lazar and E. A. Pnevmatikakis. A Stochastic Model of Olfactory Transduction. Conference on Engineering Principles in Biological Systems, December 2006. A. A. Lazar and E. A. Pnevmatikakis. A Simple Spiking Retina Model for Exact Video Stimulus Representation. The Computational Neuroscience Meeting, July 2008. A. A. Lazar and E. A. Pnevmatikakis. Consistent Recovery of Sensory Stimuli Encoded with MIMO Neural Circuits. Computational Intelligence and Neuroscience, Hindawi Publishing Corporation, February 2010. A. A. Lazar and E. A. Pnevmatikakis. Encoding of Multivariate Stimuli with MIMO Neural Circuits. Proceedings of the ISIT 2011, IEEE, July 2011. A. A. Lazar and E. A. Pnevmatikakis. A Video Time Encoding Machine. IEEE International Conference on Image Processing, pages 717-720, October 2008. A. A. Lazar and E. A. Pnevmatikakis. Reconstruction and Classification of Stimuli Encoded with Neural Circuits with Feedback. Computational Neuroscience Meeting, July 2009. A. A. Lazar and E. A. Pnevmatikakis. Multi Input Multi Output Neural Population Encoding. The Computational Neuroscience Meeting, July 2007. A. A. Lazar and E. A. Pnevmatikakis. Consistent Recovery of Stimuli Encoded with a Neural Ensemble. Proceedings of the ICASSP 2009, pages 3497-3500, April 2009. A. A. Lazar and E. A. Pnevmatikakis. Faithful Representation of Video Streams with a Population of Spiking Neurons. Computational and Systems Neuroscience Meeting, February 2008. A. A. Lazar and E. A. Pnevmatikakis. Video Time Encoding Machines. IEEE Transactions on Neural Networks, volume 22, issue 3, pages 461-473, March 2011. A. A. Lazar and L. T. Toth. Sensitivity Analysis of Time Encoded Bandlimited Signals. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 2, pages 901-904, May 2004. A. A. Lazar and L. T. Toth. Perfect Recovery and Sensitivity Analysis of Time Encoded Bandlimited Signals. IEEE Transactions on Circuits and Systems-I: Regular Papers, volume 51, issue 10, pages 2060-2073, October 2004. A. A. Lazar and L. T. Toth. Time Encoding and Perfect Recovery of Bandlimited Signals. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 6, pages 709-712, April 2003. A. A. Lazar and R. J. Turetsky. Encoding Auditory Scenes with a Population of Hodgkin-Huxley Neurons. Computational Neuroscience Meeting, July 2010. A. A. Lazar and T. Liu. An Open-Source Model of the Fruit Fly Larval Mushroom Body. Neurobiology of Drosophila, Cold Spring Harbor Laboratory, October 2017. A. A. Lazar and Y. B. Slutskiy. Identifying Dendritic Processing in Drosophila OSNs. Computational and Systems Neuroscience Meeting, February 2012. A. A. Lazar and Y. B. Slutskiy. Identifying Dendritic Processing in a [Filter]-[Hodgkin Huxley] Circuit. Computational Neuroscience Meeting, July 2011. A. A. Lazar and Y. B. Slutskiy. Identifying Dendritic Processing. Advances in Neural Information Processing Systems 23, J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta, pages 1261-1269, 2010. A. A. Lazar and Y. B. Slutskiy. Estimating Receptive Fields and Spike-Processing Neural Circuits in Drosophila. Computational Neuroscience Meeting, July 2012. A. A. Lazar and Y. B. Slutskiy. Channel Identification Machines. Journal of Computational Intelligence and Neuroscience, volume 2012, pages 1-20, July 2012. A. A. Lazar and Y. B. Slutskiy. Identification of Nonlinear-Nonlinear Neuron Models and Stimulus Decoding. Computational Neuroscience Meeting, July 2013. A. A. Lazar and Y. B. Slutskiy. Functional Identification of Spike-Processing Neural Circuits. Neural Computation, MIT Press, volume 26, issue 2, pages 264-305, February 2014. A. A. Lazar and Y. B. Slutskiy. Multisensory Encoding, Decoding, and Identification. Advances in Neural Information Processing Systems 26, C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani and K.Q. Weinberger, pages 3208-3216, December 2013. A. A. Lazar and Y. B. Slutskiy. Spiking Neural Circuits with Dendritic Stimulus Processors: Encoding, Decoding, and Identification in Reproducing Kernel Hilbert Spaces. Journal of Computational Neuroscience, volume 38, issue 1, pages 1-24, February 2015. A. A. Lazar and Y. B. Slutskiy. Channel Identification Machines for Multidimensional Receptive Fields. Frontiers in Computational Neuroscience, volume 8, issue 117, September 2014. A. A. Lazar and Y. Zhou. Encoding Visual Stimuli with a Population of Hodgkin-Huxley Neurons. Computational Neuroscience Meeting, July 2010. A. A. Lazar and Y. Zhou. Realizing Video Time Decoding Machines with Recurrent Neural Networks. Proceedings of the International Joint Conference on Neural Networks, July 2011. A. A. Lazar and Y. Zhou. Massively Parallel Neural Encoding and Decoding of Visual Stimuli. Neural Networks, volume 32, pages 303-312, August 2012. A. A. Lazar and Y. Zhou. Reconstructing Natural Visual Scenes from Spike Times. Proceedings of the IEEE, volume 102, issue 10, pages 1500-1519, October 2014. A. A. Lazar and Y. Zhou. Volterra Dendritic Stimulus Processors and Biophysical Spike Generators with Intrinsic Noise Sources. Frontiers in Computational Neuroscience, volume 8, issue 95, pages 1-24, September 2014. A. A. Lazar and Y. Zhou. Identifying Multisensory Dendritic Stimulus Processors. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, volume 2, issue 2, pages 183-198, December 2016. A. A. Lazar and Y. Zhou. Beyond the Connectome: Divisive Normalization Processors in the Drosophila Early Olfactory and Vision Systems. Computational Neuroscience Meeting, CNS*24, July 2024. A. A. Lazar and Y. Zhou. Divisive Normalization Processors in the Early Visual System of the Drosophila Brain. Biological Cybernetics, Springer, Special Issue: What can Computer Vision learn from Visual Neuroscience?, September 2023. L. E. Givon, A. A. Lazar, and C.-H. Yeh. Generating Executable Models of the Drosophila Central Complex. Frontiers in Behavioral Neuroscience, May 2017. A. G. Dimitrov, A. A. Lazar, and J. D. Victor. Information Theory in Neuroscience. Journal of Computational Neuroscience, volume 30, issue 1, pages 1-5, February 2011. M. Seok, M. Yang, Z. Jiang, A. A. Lazar, and J. Seo. Cases for Analog-Mixed-Signal Computing Integrated-Circuits for Deep Neural Networks. International Symposium on VLSI Design, Automation, and Test (VLSI-DAT), 2019. P. R. Kinget, A. A. Lazar, and L. T. Toth. On the Robustness of the VLSI Implementation of a Time Encoding Machine. IEEE International Symposium on Circuits and Systems, May 2005. O. T. Shafer, G. J. Gutierrez, K. Li, A. Mildenhall, D. Spira, J. Marty, A. A. Lazar, and M. P. Fernandez. Connectomic Analysis of the Drosophila Lateral Neuron Clock Cells Reveals the Synaptic Basis of Functional Pacemaker Classes. eLife, July 2022. D. Wang, S. J. Kim, M. Yang, A. A. Lazar, and M. Seok. A Background-Noise- and Process-Variation-Tolerant 109-nW Acoustic Feature Extractor based on Spike-Domain Divisive Energy Normalization for an Always-on Keyword Spotting Device. 2021 IEEE International Solid-State Circuits Conference (ISSCC), pages 160-162, February 2021. M. Yang, C.-H. Yeh, Y. Zhou, J. P. Cerqueira, A. A. Lazar, and M. Seok. A 1μW Voice Activity Detector Using Analog Feature Extraction and Digital Deep Neural Network. 2018 IEEE International Solid-State Circuits Conference (ISSCC), pages 346-348, February 2018. M. Yang, C.-H. Yeh, Y. Zhou, J. P. Cerqueira, A. A. Lazar, and M. Seok. Design of an Always-On Deep Neural Network Based 1 μW Voice Activity Detector Aided with a Customized Software Model for Analog Feature Extraction. IEEE Journal of Solid-State Circuits, IEEE, volume 54, issue 6, pages 1764-1777, June 2019. D. S. Chevitarese, L. E. Givon, A. A. Lazar, and M. Vellasco. CircuitML: a Modular Language for Modeling Local Processing Units in the Drosophila Brain. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013, August 2013. L. E. Givon, A. A. Lazar, and N. H. Ukani. NeuroArch: A Graph dB for Querying and Executing Fruit Fly Brain Circuits. Neurokernel Request for Comments, Neurokernel RFC #5, December 2015. L. E. Givon, A. A. Lazar, and N. H. Ukani. Neuroarch: A Graph-Based Platform for Constructing and Querying Models of the Fruit Fly Brain Architecture. Frontiers in Neuroinformatics, issue 42, August 2014. A. J. Kim, A. A. Lazar, and Y. B. Slutskiy. System Identification of Drosophila Olfactory Sensory Neurons. Journal of Computational Neuroscience, Springer, volume 30, issue 1, pages 143-161, February 2011. A. J. Kim, A. A. Lazar, and Y. B. Slutskiy. Drosophila Projection Neurons Encode the Acceleration of Time-Varying Odor Waveforms. Computational and Systems Neuroscience Meeting, February 2011. A. J. Kim, A. A. Lazar, and Y. B. Slutskiy. Investigating Odor Identity Encoding in Drosophila OSNs. Computational and Systems Neuroscience Meeting, February 2011. A. J. Kim, A. A. Lazar, and Y. B. Slutskiy. Projection Neurons in Drosophila Antennal Lobes Signal the Acceleration of Odor Concentrations. eLife 2015;10.7554/eLife.06651, June 2015. A. J. Kim, A. A. Lazar, and Y. Slutskiy. 2D Encoding of Concentration and Concentration Gradient in Drosophila ORNs. Computational and Systems Neuroscience Meeting, February 2010. A. J. Kim, A. A. Lazar, and Y. Slutskiy. System Identification of the DM4 Glomerulus in the Drosophila Antennal Lobe. Computational Neuroscience Meeting, July 2010. B. Y. Bu, A. A. Lazar, and Y. Zhou. Evaluating with Natural Scenes the End-to-End Motion Detection of the Drosophila Early Visual System. Neurobiology of Drosophila, Cold Spring Harbor Laboratory, October 2023. B. Y. Bu, A. A. Lazar, and Y. Zhou. End-to-End Modeling of the Drosophila Early Vision System with Cascading Divisive Normalization Processors. Neuroscience 2024, Society for Neuroscience, October 2024. A. A. Lazar, E. A. Pnevmatikakis, and Y. Zhou. The Power of Connectivity: Identity Preserving Transformations on Visual Streams in the Spike Domain. Neural Networks, volume 44, pages 22-35, 2013. A. A. Lazar, E. A. Pnevmatikakis, and Y. Zhou. Encoding Natural Scenes with Neural Circuits with Random Thresholds. Vision Research, volume 50, issue 22, pages 2200-2212, October 2010. A. A. Lazar, E. K. Simonyi, and L. T. Toth. An Overcomplete Stitching Algorithm for Time Decoding Machines. IEEE Transactions on Circuits and Systems-I: Regular Papers, volume 55, issue 9, pages 2619-2630, October 2008. C. Kaldy, A. A. Lazar, E. K. Simonyi, and L. T. Toth. Time Encoded Communications for Human Area Network Biomonitoring. BNET Technical Report #2-0, June 2007. A. A. Lazar, E. K. Simonyi, and L. T. Toth. A Real-Time Algorithm for Time Decoding Machines. 14th European Signal Processing Conference, September 2006. A. A. Lazar, E. K. Simonyi, and L. T. Toth. A Toeplitz Formulation of a Real-Time Algorithm for Time Decoding Machines. Proceedings of the Conference on Telecommunication Systems, Modeling and Analysis, November 2005. A. A. Lazar, E. K. Simonyi, and L. T. Toth. Fast Recovery Algorithms of Time Encoded Bandlimited Signals. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 4, pages 237-240, March 2005. A. A. Lazar, E. K. Simonyi, and L. T. Toth. Time Encoding of Bandlimited Signals, An Overview. Proceedings of the Conference on Telecommunication Systems, Modeling and Analysis, November 2005. A. A. Lazar, K. Psychas, N. H. Ukani, and Y. Zhou. Retina of the Fruit Fly Eyes: A Detailed Simulation Model. BMC Neuroscience, volume 16 (Suppl 1), pages 301, July 2015. A. A. Lazar, K. Psychas, N. H. Ukani, and Y. Zhou. A Parallel Processing Model of the Drosophila Retina. Neurokernel Request for Comments, Neurokernel RFC #3, August 2015. L. E. Givon, A. A. Lazar, K. Psychas, N. H. Ukani, C.-H. Yeh, and Y. Zhou. Neurokernel: Building an in Silico Fruit Fly Brain. IEEE EMBS BRAIN Grand Challenges Conference, IEEE, November 2014. A. A. Lazar, M. K. Turkcan, and Y. Zhou. Interrogating the Functional Logic of Drosophila Brain Circuits at Single-Synapse Scale. Society of Neuroscience, November 2021. A. A. Lazar, M. K. Turkcan, and Y. Zhou. Generating Executable Mushroom Body and Lateral Horn Circuits from the Hemibrain Dataset with FlyBrainLab. BMC Neuroscience 2020, 21(Suppl 1):P105, CNS*2020, July 2020. A. A. Lazar, M. K. Turkcan, and Y. Zhou. Untangling the Graph Structure of Drosophila Brain Datasets with Open Source FlyBrainLab Utility Libraries. Society of Neuroscience, November 2021. A. A. Lazar, M. K. Turkcan, and Y. Zhou. NeuroNLP Gene Match—An Open Source Genetic Data Visualizer and Explorer. Neurobiology of Drosophila, October 2021. A. A. Lazar, M. K. Turkcan, and Y. Zhou. A Programmable Ontology Encompassing the Functional Logic of the Drosophila Brain. Frontiers in Neuroinformatics, Neuroinformatics of Large Scale Brain Modelling, June 2022. A. A. Lazar, M. K. Turkcan, and Y. Zhou. A Programmable Ontology Encompassing the Functional Logic of the Drosophila Brain. bioRxiv, December 2021. A. A. Lazar, M. K. Turkcan, and Y. Zhou. A Programmable Model for Exploring the Functional Logic of the Drosophila Mushroom Body. bioRxiv, September 2022. A. A. Lazar, M. K. Turkcan, and Y. Zhou. A Programmable Model for Exploring the Functional Logic of the Drosophila Antennal Lobe. bioRxiv, September 2022. A. A. Lazar, N. H. Ukani, and Y. Zhou. The Cartridge: A Canonical Neural Circuit Abstraction of the Lamina Neuropil -- Construction and Composition Rules. Neurokernel Request for Comments, Neurokernel RFC #2, January 2014. A. A. Lazar, N. H. Ukani, and Y. Zhou. Modeling Contrast Gain Control of Fly Photoreceptors. 27th Computational Neuroscience Meeting, 2018. A. A. Lazar, N. H. Ukani, and Y. Zhou. Functional Identification of Complex Cells from Spike Times and the Decoding of Visual Stimuli. BMC Neuroscience, volume 16 (Suppl 1), pages 300, July 2015. A. A. Lazar, N. H. Ukani, and Y. Zhou. Sparse Identification of Contrast Gain Control in the Fruit Fly Photoreceptor and Amacrine Cell Layer. The Journal of Mathematical Neuroscience, Springer Open, volume 10, issue 3, February 2020. A. A. Lazar, N. H. Ukani, and Y. Zhou. Sparse Functional Identification of Complex Cells from Spike Times and the Decoding of Visual Stimuli. The Journal of Mathematical Neuroscience, volume 8, issue 2, pages 1-40, January 2018. A. A. Lazar, N. H. Ukani, and Y. Zhou. A General Model for Divisive Normalization and its Identification. Society for Neuroscience Abstracts, November 2017. A. A. Lazar, N. H. Ukani, and Y. Zhou. Sparse Functional Identification of Complex Cells from Spike Times and the Decoding of Visual Stimuli. Neurons and Cognition, arXiv.org, June 2017. A. A. Lazar, N. H. Ukani, and Y. Zhou. Sparse Identification of Contrast Gain Control in the Fruit Fly Photoreceptor and Amacrine Cell Layer. Neurons and Cognition, arXiv, October 2019. A. A. Lazar, N. H. Ukani, and Y. Zhou. A Motion Detection Algorithm Using Local Phase Information. Computational Intelligence and Neuroscience, volume 2016, Article ID 7915245, January 2016. A. A. Lazar, N. H. Ukani, C.-H. Yeh, and Y. Zhou. A Parallel Programming Model of Local Processing Units in the Fruit Fly Brain. Frontiers in Neuroinformatics, issue 24, August 2014. A. A. Lazar, N. H. Ukani, C.-H. Yeh, and Y. Zhou. NeuroGFX: A Graphical Functional Explorer for Fruit Fly Brain Circuits. Society for Neuroscience Abstracts, November 2017. N. Anerousis, P. Chemouil, A. A. Lazar, N. Mihai, and S. B. Weinstein. The Origin and Evolution of Open Programmable Networks and SDN. IEEE Communications Surveys and Tutorials, volume 23, issue 3, February 2021. A. G. Dimitrov, F. Fekri, A. A. Lazar, S. M. Moser, and P. J. Thomas. Guest Editorial: Biological Applications of Information Theory in Honor of Claude Shannon's Centennial, Part II. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, Special Issue on Biological Applications of Information Theory in Honor of Claude Shannon’s Centennial—Part 1, volume 2, issue 2, pages 117-119, December 2016. A. G. Dimitrov, F. Fekri, A. A. Lazar, S. M. Moser, and P. J. Thomas. Guest Editorial: Biological Applications of Information Theory in Honor of Claude Shannon's Centennial, Part I. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, volume 2, issue 1, pages 1-4, June 2016. A. A. Lazar, S. Shukla, and Y. Zhou. Modeling Small Object Detection of Drosophila Lobula Circuits with Divisive Normalization Processors. Neuroscience 2024, Society for Neuroscience, October 2024. B. Y. Bu, P. I. Deevi, A. A. Lazar, S. Shukla, and Y. Zhou. DrosoGPT: a Natural Language Querying Interface for Exploring the Structure and Functional Logic of the Drosophila Brain. Neuroscience 2024, Society of Neuroscience, October 2024. A. A. Lazar, S. Shukla, and Y. Zhou. Generating Wiring Diagrams of Local Processing Units of the Drosophila Central Complex. Neurobiology of Drosophila, Cold Spring Harbor Laboratory, October 2023. A. A. Lazar, T. Liu, and C.-H. Yeh. The Geometry of Spatio-Temporal Odorant Mixture Encoding in the Drosophila Mushroom Body. BMC Neuroscience 2020, 21(Suppl 1):P218, CNS*2020, July 2020. A. A. Lazar, T. Liu, and C.-H. Yeh. An Odorant Encoding Machine for Sampling, Reconstruction and Robust Representation of Odorant Identity. ICASSP 2020, pages 1743-1747, May 2020. A. A. Lazar, T. Liu, and C.-H. Yeh. The Functional Logic of Odor Information Processing in the Drosophila Antennal Lobe. bioRxiv , December 2021. A. A. Lazar, T. Liu, and C.-H. Yeh. The Functional Logic of Odor Information Processing in the Drosophila Antennal Lobe. PLOS Computational Biology, volume 19, issue 4, April 2023. A. A. Lazar, T. Liu, and Y. Zhou. Divisive Normalization Circuits Faithfully Represent Visual, Olfactory and Auditory Stimuli. BMC Neuroscience 2019, 20 (Suppl 1): P353, 28th Annual Computational Neuroscience Meeting, 2019. A. A. Lazar, T. Liu, and Y. Zhou. Functional Identification of the Odorant Transduction Process of Drosophila Olfactory Sensory Neurons. BMC Neuroscience 2020, 21(Suppl 1):P225, CNS*2020, July 2020. A. A. Lazar, T. Liu, and Y. Zhou. Divisive Normalization Circuits Faithfully Represent Auditory and Visual Stimuli. bioRxiv, September 2022. A. A. Lazar, T. Liu, C.-H. Yeh, and Y. Zhou. Divisive Normalization Processing Underlies Odorant Mixture Representation in the Mushroom Body Calyx. Neuroscience 2024, Society of Neuroscience, October 2024. A. A. Lazar, T. Liu, C.-H. Yeh, and Y. Zhou. Odorant Mixture Separation in the Drosophila Mushroom Body Calyx. Neurobiology of Drosophila, Cold Spring Harbor Laboratory, October 2023. A. A. Lazar, T. Liu, C.-H. Yeh, and Y. Zhou. Modeling and Characterization of Pure and Odorant Mixture Processing in the Drosophila Mushroom Body Calyx. Frontiers in Physiology: Invertebrate Physiology, Research Topic: Invertebrate Brains as Model Systems for Learning, Memory, and Recall: Development, Anatomy and Function of Memory Systems, volume 15, October 2024. A. A. Lazar, T. Liu, C.-H. Yeh, and Y. Zhou. Odorant Mixture Separation in Drosophila Early Olfactory System. bioRxiv, September 2022. A. A. Lazar, T. Liu, M. K. Turkcan, and Y. Zhou. 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