The main goal of this project is to make a significant contribution to the scientific community. To do this, it is important to share and disseminate outcomes to researchers and the public alike. All publications and models to date are posted.
Cope A., Sabo C., Gurney K., Vasilaki E., and Marshall J. A. R. (2016), “A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee,” PLoS Computational Biology. doi:10.1371/journal.pcbi.1004887.s001
Yavuz, E., Turner, J. and Nowotny, T. (2016), “GeNN: a code generation framework for accelerated brain simulations”, Scientific Reports, Nature Publishing Group, vol. 6, 18854. doi:10.1038/srep18854
Berdan, R., Vasilaki, E., Wei, S. L., Khiat, A., Indiveri, G., Lim, C., Salaoru, I. and Prodromakis, T. (2016), “Emulating short-term synaptic dynamics with memristive devices”, Scientific Reports, Nature Publishing Group, vol. 6, 18639. doi:10.1038/srep18639
Wu G., Nowotny T., Chen Y. and Li D. (2016) “GPU acceleration of time-domain fluorescence lifetime imaging”, Journal of Biomedical Optics. doi:10.1117/1.JBO.21.1.017001
Barron A. B., Gurney K. N., Meah L. F. S., Vasilaki E. and Marshall J. A. R. (2015), “Decision-making and action selection in insects: inspiration from vertebrate-based theories”, Frontiers in Behavioral Neuroscience, 9:216. doi: 10.3389/fnbeh.2015.00216
Esposito U., Giugliano M. and Vasilaki E. (2015), “Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity”, Frontiers in Computational Neuroscience,” 8:175. doi: 10.3389/fncom.2014.00175
Caballero J.A., Lepora N.F. and Gurney K.N. (2015) “Probabilistic Decision Making with Spikes: From ISI Distributions to Behaviour via Information Gain.” PLoS ONE. doi: 10.1371/journal.pone.0124787
Vasilaki, E. and Gugliano, M. (2014), “Emergence of Connectivity Motifs in Networks of Model Neurons with Short- and Long-term Plastic Synapses”, PLoS ONE, 9(1): e84626. doi:10.1371/journal.pone.0084626
Esposito, U., van Rossum, M., Giugliano, M., and Vasilaki, E. (2014), “Measuring Symmetry, Asymmetry and Randomness in Neural Networks”, PLoS ONE, 9(7): e100805. doi:10.1371/journal.pone.0100805.
Nowotny T., de Bruyne M., Berna A.Z., Warr C.G. and Trowell S.C. (2014), “Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications”, Bioinspiration & Biomimetics. doi:10.1088/1748-3182/9/4/046007
Nowotny T. (2014), “Two Challenges of Correct Validation in Pattern Recognition”, Frontiers in Robotics and AI. doi:10.3389/frobt.2014.00005
Nowotny T., Stierle J. S., Galizia C. G. and Szyszka P. (2013) “Data-driven Honeybee Antennal Lobe Model Suggests how Stimulus-Onset Asynchrony can aid Odour Segregation”, Brain Research, Elsevier. doi:10.1016/j.brainres.2013.05.038
Serrano E., Nowotny T., Levi R., Smith B.H. and Huerta R. (2013) “Gain control network conditions in early sensory coding”, PLoS computational biology. doi:10.1371/journal.pcbi.1003133
Nowotny T., Rospars J-P., Martinez D., Elbanna S. and Anton S. (2013) “Machine learning for automatic prediction of the quality of electrophysiological recordings”, PLoS ONE. doi:10.1371/journal.pone.0080838
C. Sabo, A. Cope, K. Gurny, E. Vasilaki, and J. A. R. Marshall, “Bio-Inspired Visual Navigation for a Quadcopter using Optic Flow,” AIAA Infotech@Aerospace, San Diego, January, 2016, AIAA 2016-0404.
A. Simpson and C. Sabo, “Quadcopter Obstacle Avoidance using Biomimetic Algorithms,” AIAA Infotech@Aerospace, San Diego, January, 2016, AIAA 2016-0403.
Conference Posters & Presentations
A. Cope, C. Sabo, E. Vasilaki, K. Gurney, J. Marshall, “A neural model of the optomotor system accounts for ordered responses to decreasing stimulus spatial frequencies,” BMC Neuroscience, Computational Neuroscience Meeting, Vol. 16, Suppl 1, p. 159, Prague, July, 2015, DOI: 10.1186/1471-2202-16-S1-P159.
E. Yavuz, P. Maul, and T. Nowotny, “Spiking neural network model of reinforcement learning in the honeybee implemented on the GPU,” BMC Neuroscience, Computational Neuroscience Meeting, Vol. 16, Suppl 1, p. 181, Prague, July, 2015. CNS 2015 Yavuz
T. Nowotny, J. Turner, and E. Yavuz, “More flexibility for code generation with GeNN v2.1”, BMC Neuroscience, Computational Neuroscience Meeting, Vol. 16, Suppl 1, p. 291, Prague, July, 2015. CNS 2015 Nowotny
E. Yavuz and T. Nowotny, “A modelling framework for the olfactory system of the honeybee using GeNN (GPU-enhanced neuronal network simulation environment),” Flavour, Odor Space Conference, Vol. 3, Suppl 1, p. P23, Hannover, September, 2014.
T. Nowotny, C. G. Galizia and P. Szyszka, “Stimulus-onset asynchrony can aid odor segregation”, Flavour, Odor Spaces Conference, Vol. 3, Suppl 1, p. P12, Hannover, September, 2014.
E. Yavuz, J. Turner and T. Nowotny, “Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN”, Bernstein Conference, Goettingen, September 2014. BCCN 2014 Yavuz
C. Sabo, “Bio-Inspired Visual Navigation of a Quadcopter using Optic Flow”, World Congress on Unmanned Systems Engineering, Oxford, July 2014.
O. Merry and C. Sabo, “Using Optic Flow for Navigation of an Autonomous Quadcopter”, World Congress on Unmanned Systems Engineering, Oxford, July 2014.
T. Nowotny, A. J. Cope, E. Yavuz, M. Stimberg, D. F. Goodman, J. Marshall, and K. Gurney, “SpineML and Brian 2.0 interfaces for using GPU-enhanced neuronal networks (GeNN),” BMC Neuroscience, Computational Neuroscience Meeting, Vol. 15, Suppl 1, p. 148, Quebec City, July, 2014.
E. Yavuz, J. Turner, and T. Nowotny, “Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN,” BMC Neuroscience, Computational Neuroscience Meeting, Vol. 15, Suppl 1, p. O1, Quebec City, July, 2014.
E. Yavuz, A. Cope, L. Meah, C. Sabo, K. Gurney, J. Marshall, E. Vasilaki, and T. Nowotny, “Towards Real-Time Models of Full-Size Insect Brains using GPU-Enhanced Neuronal Network Simulations (GeNN),” Invertebrate Neurobiology Workshop, Toulouse, France, May, 2014. IN Toulouse 2014 Yavuz
A. Cope, P. Richmond, J. A. R.Marshall, and D. Allerton, “Creating and Simulating Neural Networks in the Honeybee Brain using a Graphical Toolchain,” Society for Neuroscience Annual Meeting, San Diego, November, 2013, SFN_2013_GB.
A. Cope, C. Sabo, E. Yavuz, K. Gurney, J. Marshall, T. Nowotny, and E. Vasilaki, “The Green Brain Project – Developing a Neuromimetic Robotic Honeybee,” Living Machines Conference, London, August, 2013, Living_Machines_2013_GB.