The “Brains on Board” team supports open-access publishing and aims to share and disseminate outcomes to researchers and the public alike. BoB publications will be populated further as the project matures. See the publications thus far which have been attributed to BoB:
“Brains on Board” Publications
Vasas, V. and Chittka, L. (2019) Insect-Inspired Sequential Inspection Strategy Enables an Artificial Network of Four Neurons to Estimate Numerosity. iScience, Vol 11, 85-92. doi: 10.1016/j.isci.2018.12.009
Cope A.J., Vasilaki E., Minors D., Sabo C., Marshall, J.A.R. and Barron, A.B. (2018) Abstract concept learning in a simple neural network inspired by the insect brain. PLoS Comput Biol 14(9). doi: 10.1371/journal.pcbi.1006435.
Knight J.C. and Nowotny T. (2018) GPUs outperform Current HPC and Neuromorphic Solutions in Terms of Speed and Energy When Simulating a Highly-Connected Cortical Model. Frontiers in Neuroscience, 12:941. doi: 10.3389/fnins.2018.00941
Guiraud M., Roper M. and Chittka, L. (2018) High-speed Videography Reveals How Honeybees Can Turn a Spatial Concept Learning Task Into a Simple Discrimination Task by Stereotyped Flight Movements. Frontiers in Psychology, Vol 9, 1347. doi: 10.3389/fpsyg.2018.01347
Woodgate, J.L., Makinson, J.C., Lim, K.S., Reynolds A.M. and Chittka, L. (2017) Continuous Radar Tracking Illustrates the Development of Multi-destination Routes of Bumblebees. Scientific Reports, 7, 17323. doi:10.1038/s41598-017-17553-1
C. Sabo, R. Chisholm, A. Petterson, A. Cope, A lightweight, inexpensive robotic system for insect vision (2017), Arthropod Structure & Development, ISSN 1467-8039, http://dx.doi.org/10.1016/j.asd.2017.08.001
A. Cope, C. Sabo, E. Vasilaki, A. B. Barron, and J. A. R. Marshall (2017), “A Computational Model of the Integration of Landmarks and Motion in the Insect Central Complex,” PLoS One, Feb. 27. doi: 10.1371/journal.pone.0172325
Sabo C., Yavuz E., Cope A., Gurney K., Vasilaki E., Nowotny T., and Marshall J. A. R. (2017) An Inexpensive Flying Robot Design for Embodied Robotics Research. 2017 International Joint Conference on Neural Networks. Anchorage, Alaska, May 14-19.
Peng F. & Chittka L. (2017) A Simple Computational Model of the Bee Mushroom Body Can Explain Seemingly Complex Forms of Olfactory Learning and Memory. Current Biology 27(2): 224-230. doi: 10.1016/j.cub.2016.10.054.
Roper M., Fernando C. & Chittka L. (2017) Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees. PLoS Comput Biol 13(2): e1005333. doi:10.1371/journal.pcbi.1005333.
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-Centring 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.
Sabo C., Cope A., Gurney K., Vasilaki E., and Marshall J. A. R. (2016). Bio-Inspired Visual Navigation for a Quadcopter using Optic Flow. AIAA Infotech@Aerospace. San Diego, CA, Jan., AIAA 2016-0404.
Additionally, please review the published outcomes from the “Green Brain Project” here: www.greenbrainproject.co.uk/publications/