Michael Beyeler

Advisors:Ione Fine,Geoffrey Boynton

Email: mbeyeler "at" uw.edu

CV: MichaelBeyeler_CV.pdf

My research focuses on developing and testing neurophysiologically inspired algorithms for improved stimulation protocols in patients implanted with retinal prostheses.


Beyeler M., Rokem A., Boynton G. and Fine I. (2017). Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies. J Neural Eng, . | Reprint 1.82MB pdf |

Beyeler M., Dutt N. and Krichmar J.L. (2016). 3D Visual Response Properties of MSTd Emerge from an Efficient, Sparse Population Code. J Neurosci, 36(32), 8399-415. | Reprint 2.00MB pdf |

Beyeler M., Oros N., Dutt N. and Krichmar J.L. (2015). A GPU-accelerated cortical neural network model for visually guided robot navigation. Neural Netw, 72, 75-87. | Reprint 6.31MB pdf |

Beyeler M., Richert M., Dutt N.D. and Krichmar J.L. (2014). Efficient spiking neural network model of pattern motion selectivity in visual cortex. Neuroinformatics, 12(3), 435-54. | Reprint 479KB pdf |

Beyeler M., Dutt N.D. and Krichmar J.L. (2013). Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule. Neural Netw, 48, 109-24. | Reprint 1.91MB pdf |