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

MaBouDi, H., Marshall, J.A.R., Barron, A.B. (2020) Honeybees solve a multi-comparison ranking task by probability matching. Proceedings of the Royal Society Series B. doi:10.1098/rspb.2020.1525

Stimberg, M., Goodman, D., & Nowotny, T. (2020). Brian2GeNN: accelerating spiking neural network simulations with graphics hardware. Scientific Reports, 10, 410. doi:10.1038/s41598-019-54957-7

Li, X., Abou Tayoun, A., Song, Z., Dau, A., Rien, D., Jaciuch, D., Dongre, S., Blanchard, F., Nikolaev, A., Zheng, L., Bollepalli, M.K., Chu, B., Hardie, R.C., Dolph, P.J., & Juusola, M. (2019). Ca2+-activated K+ channels reduce network excitability, improving adaptability and energetics for transmitting and perceiving sensory information. Journal of Neuroscience, 39 (36), 7132-7154. doi:10.1523/JNEUROSCI.3213-18.2019

Perry, C., & Chittka, L. (2019). How foresight might support the behavioural flexibility of arthropods. Current Opinion in Neurobiology, 54, 171-177. doi:10.1016/j.conb.2018.10.014

Vasas, V., Peng, F., MaBouDi, H., & Chittka, L. (2019) Randomly weighted receptor inputs can explain the large diversity of colour-coding neurons in the bee visual system. Scientific Reports, 9:8330. doi:10.1038/s41598-019-44375-0

Makinson, J.C., Woodgate, J.L., Reynolds, A., Capaldi, E.A., Perry, C.J., & Chittka, L. (2019) Harmonic radar tracking reveals random dispersal pattern of bumblebee (Bombus terrestris) queens after hibernation. Scientific Reports, 9:4651. doi:10.1038/s41598-019-40355-6

Vasas, V., & 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., & 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., & 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., & 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, 900. doi: 10.3389/fpsyg.2018.01347

Gallo, V., & Chittka, L. (2018) Cognitive Aspects of Comb-Building in the Honeybee? Frontiers in Psychology, Vol 9, 1347. doi: 10.3389/fpsyg.2018.00900

Woodgate, J.L., Makinson, J.C., Lim, K.S., Reynolds A.M., & 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

Sabo, C., Chisholm, R., Petterson, A., & Cope, A. (2017). A lightweight, inexpensive robotic system for insect vision, Arthropod Structure & Development, ISSN 1467-8039,

Cope, A., Sabo, C., Vasilaki, E., Barron, A. B., & Marshall, J. A. R. (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., & 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.

Related Publications

Wystrach, A., Schwarz, S., Graham, P., & Cheng, K.(2019). Running paths to nowhere: repetition of routes shows how navigating ants modulate online the weights according to cues. Animal Cognition 22(2), 213-222. doi:10.1007/s10071-019-01236-7

Johnson, C., Philippides, A., & Husbands, P. (2019). Simulating soft-bodied swimmers with particle-based physics. Soft Robotics, 6 (2), 263-275. doi:10.1089/soro.2018.0027

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., & 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., & 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., & 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: