Publications

The main goal of the Green Brain project was to make a significant contribution to the scientific community, therefore it is important to share and disseminate outcomes to researchers and the public alike. All publications and models are posted here.

On

Journal articles

Cope A., Sabo C., Gurney K., Vasilaki E., and Marshall J. A. R. (2016), 鈥淎 Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee鈥 PLoS Computational Biology.

Yavuz, E., Turner, J. and Nowotny, T. (2016), 鈥淕eNN: a code generation framework for accelerated brain simulations鈥, Scientific Reports, Nature Publishing Group, vol. 6,  18854.

Berdan, R., Vasilaki, E., Wei, S. L., Khiat, A., Indiveri, G., Lim, C., Salaoru, I. and Prodromakis, T. (2016), 鈥淓mulating short-term synaptic dynamics with memristive devices鈥, Scientific Reports, Nature Publishing Group, vol. 6, 18639.

Wu G., Nowotny T., Chen Y. and Li D. (2016) 鈥淕PU acceleration of time-domain fluorescence lifetime imaging鈥, Journal of Biomedical Optics.

Barron A. B., Gurney K. N., Meah L. F. S., Vasilaki E. and Marshall J. A. R. (2015), 鈥淒ecision-making and action selection in insects: inspiration from vertebrate-based theories鈥, Frontiers in Behavioral Neuroscience, 9:216.

Esposito U., Giugliano M. and Vasilaki E. (2015), 鈥淎daptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity鈥, Frontiers in Computational Neuroscience,鈥 8:175.

Caballero J.A., Lepora N.F. and Gurney K.N. (2015) 鈥淧robabilistic Decision Making with Spikes: From ISI Distributions to Behaviour via Information Gain.鈥 PLoS ONE.

Vasilaki, E. and Gugliano, M. (2014), 鈥淓mergence of Connectivity Motifs in Networks of Model Neurons with Short- and Long-term Plastic Synapses鈥, PLoS ONE, 9(1): e84626.

Serrano E., Nowotny T., Levi R., Smith B.H. and Huerta R. (2013) 鈥淕ain control network conditions in early sensory coding鈥, PLoS computational biology.

Nowotny T., Rospars J-P., Martinez D., Elbanna S. and Anton S. (2013) 鈥淢achine learning for automatic prediction of the quality of electrophysiological recordings鈥, PLoS ONE.


Conference papers

C. Sabo, A. Cope, K. Gurny, E. Vasilaki, and J. A. R. Marshall, 鈥淏io-Inspired Visual Navigation for a Quadcopter using Optic Flow鈥 AIAA Infotech@Aerospace, San Diego, January, 2016, .

A. Simpson and C. Sabo, 鈥淨uadcopter Obstacle Avoidance using Biomimetic Algorithms鈥 AIAA Infotech@Aerospace, San Diego, January, 2016, .


Conference posters and presentations

A. Cope, C. Sabo, E. Vasilaki, K. Gurney, J. Marshall, 鈥淎 neural model of the optomotor system accounts for ordered responses to decreasing stimulus spatial frequencies鈥&苍产蝉辫;BMC Neuroscience, Computational Neuroscience Meeting, Vol. 16, Suppl 1, p. 159, Prague, July, 2015,.

E. Yavuz, P. Maul, and T. Nowotny, 鈥淪piking neural network model of reinforcement learning in the honeybee implemented on the GPU鈥 BMC Neuroscience, Computational Neuroscience Meeting, Vol. 16, Suppl 1, p. 181, Prague, July, 2015. 

T. Nowotny, J. Turner, and E. Yavuz, 鈥淢ore flexibility for code generation with GeNN v2.1鈥BMC Neuroscience, Computational Neuroscience Meeting, Vol. 16, Suppl 1, p. 291, Prague, July, 2015. 

E. Yavuz and T. Nowotny, 鈥淎 modelling framework for the olfactory system of the honeybee using GeNN (GPU-enhanced neuronal network simulation environment)鈥 Flavour, Odor Space Conference, Vol. 3, Suppl 1, p. P23, Hannover, September, 2014.

T. Nowotny, C. G. Galizia and P. Szyszka, 鈥淪timulus-onset asynchrony can aid odor segregation鈥Flavour, Odor Spaces Conference, Vol. 3, Suppl 1, p. P12, Hannover, September, 2014.

E. Yavuz, J. Turner and T. Nowotny, 鈥淪imulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN鈥, Bernstein Conference, Goettingen, September 2014. 

C. Sabo, 鈥淏io-Inspired Visual Navigation of a Quadcopter using Optic Flow鈥, World Congress on Unmanned Systems Engineering, Oxford, July 2014.

O. Merry and C. Sabo, 鈥淯sing Optic Flow for Navigation of an Autonomous Quadcopter鈥, 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, 鈥淪pineML and Brian 2.0 interfaces for using GPU-enhanced neuronal networks (GeNN)鈥 BMC Neuroscience, Computational Neuroscience Meeting, Vol. 15, Suppl 1, p. 148, Quebec City, July, 2014.

E. Yavuz, J. Turner, and T. Nowotny, 鈥淪imulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN鈥 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, 鈥淭owards Real-Time Models of Full-Size Insect Brains using GPU-Enhanced Neuronal Network Simulations (GeNN)鈥 Invertebrate Neurobiology Workshop, Toulouse, France, May, 2014. 

A. Cope, P. Richmond, J. A. R.Marshall, and D. Allerton, 鈥淐reating and Simulating Neural Networks in the Honeybee Brain using a Graphical Toolchain鈥 Society for Neuroscience Annual Meeting, San Diego, November, 2013, .

A. Cope, C. Sabo, E. Yavuz, K. Gurney, J. Marshall, T. Nowotny, and E. Vasilaki, 鈥淭he Green Brain Project 鈥 Developing a Neuromimetic Robotic Honeybee鈥 Living Machines Conference, London, August, 2013, .