Publications about Nengo
Below are publications about Nengo itself. If you want to cite Nengo, please use the first entry in this list.
Bekolay, Bergstra, Hunsberger, DeWolf, Stewart, Rasmussen, Choo, Voelker & Eliasmith. (2014) Nengo: a Python tool for building large-scale functional brain models. Frontiers in Neuroinformatics 7. PDF
Sharma, Aubin & Eliasmith. (2016) Large-scale cognitive model design using the Nengo neural simulator. Biologically Inspired Cognitive Architectures 17 (2016): 86-100. PDF
Gosmann & Eliasmith. (2017) Automatic optimization of the computation graph in the Nengo neural network simulator. Frontiers in Neuroinformatics 11. PDF
Rasmussen. (2018) NengoDL: Combining deep learning and neuromorphic modelling methods. ArXiv 1805.11144. PDF
Morcos, B. (2019). NengoFPGA: an FPGA Backend for the Nengo Neural Simulator. UWSpace. website
Publications using Nengo
Below are a small selection of publications that use Nengo. Nengo has been used in over 100 publications; for a partial list, see the CNRGlab website.
Eliasmith et al. (2012). A large-scale model of the functioning brain. Science Vol. 338 no. 6111 pp. 1202-1205. DOI: 10.1126/science.1225266.
Crawford, Gingerich & Eliasmith. (2015) Biologically plausible, human-scale knowledge representation. Cognitive Science, <DOI:10.1111/cogs.12261>.
Eliasmith, Gosmann & Choo. (2016) Biospaun: a large-scale behaving brain model with complex neurons. ArXiv. PDF
Publications from Nengo summer school
Several projects from the Nengo summer school have been published or presented at conferences, or have acknowledged the summer school as a source of ideas.
Kröger, Bekolay, & Eliasmith. (2014) Modeling speech production using the Neural Engineering Framework. In 5th IEEE Conference on Cognitive Infocommunications, pp. 203-208. PDF
Senft et al. (2016) Reduction of dopamine in basal ganglia and its effects on syllable sequencing in speech: a computer simulation study. Basal Ganglia, 6.1, 7-17. PDF
Friedl et al. (2016) Human-inspired neurorobotic system for classifying surface textures by touch. Robotics and Automation Letters, 1.1, 516-523. PDF
Knight et al. (2016) Efficient SpiNNaker simulation of a heteroassociative memory using the Neural Engineering Framework. The 2016 International Joint Conference on Neural Networks (IJCNN), IEEE. PDF
Blouw, Eliasmith, & Tripp (2016) A scaleable spiking neural model of action planning. In Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. PDF
Kröger, Crawford, Bekolay, & Eliasmith (2016) Modeling interactions between speech production and perception: speech error detection at semantic and phonological levels and the inner speech loop. Frontiers in Computational Neuroscience 10:51. Full text
Borst, Aubin, & Stewart (2018) Effective computing in the brain: a whole-task spiking neural network model of associative recognition. Cognitive Computing. Philadelphia, Pennsylvania. PDF
Ororbia (2019) Spiking Neural Predictive Coding for Continual Learning from Data Streams. arXiv 1908.08655. PDF
Below are some of the popular press articles that reference Nengo.
- UWaterloo Faculty of Arts: How to Build a Brain: Chris Eliasmith publishes the book and shares tools for further discoveries
- The Record: UW prof teaches readers how to build a brain
- The Record: University “brain camp” showcases robots
- Motherboard: How to make a human brain in Python
- Futurism: Interview: Chris Eliasmith talks reverse engineering the brain, dangerous AI, and universal basic income
- Wired UK: The future of AI is neuromorphic. Meet the scientists building digital “brains” for your phone