P
Patrick Degenaar
Researcher at Newcastle University
Publications - 158
Citations - 2671
Patrick Degenaar is an academic researcher from Newcastle University. The author has contributed to research in topics: Optogenetics & Image processing. The author has an hindex of 23, co-authored 155 publications receiving 2300 citations. Previous affiliations of Patrick Degenaar include University of Newcastle & Kyungpook National University.
Papers
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Journal ArticleDOI
Multi-site optical excitation using ChR2 and micro-LED array
Nir Grossman,Vincent Poher,Matthew S. Grubb,Gordon T. Kennedy,Konstantin Nikolic,Brian McGovern,Rolando Berlinguer Palmini,Zheng Gong,Emmanuel M. Drakakis,Mark A. A. Neil,Martin D. Dawson,Juan Burrone,Patrick Degenaar +12 more
TL;DR: In this article, an array of high-power micro light-emitting diodes (micro-LEDs) is used to generate arbitrary optical excitation patterns on a neuronal sample with micrometre and millisecond resolution.
Journal ArticleDOI
Photocycles of Channelrhodopsin‐2
Konstantin Nikolic,Nir Grossman,Matthew S. Grubb,Juan Burrone,Chris Toumazou,Patrick Degenaar +5 more
TL;DR: The crucial insight provided by the analysis of the new model is that it reveals an adaptation mechanism of the ChR2 molecule, which means very simple organisms expressing ChR1 can use this form of light adaptation.
Journal ArticleDOI
Micro-LED arrays: a tool for two-dimensional neuron stimulation
Vincent Poher,Nir Grossman,Gordon T. Kennedy,Konstantin Nikolic,H.X. Zhang,Zheng Gong,Emmanuel M. Drakakis,Erdan Gu,Martin D. Dawson,Paul M. W. French,Patrick Degenaar,Mark A. A. Neil +11 more
TL;DR: A GaN based micro-light emitting diode (LED) array that can open the way to multi- site photostimulation of neuron cells and a complete system that combines the micro-LED array with multi-site electrophysiological recording based on microelectrode array technology and/or fluorescence imaging is presented.
Journal ArticleDOI
Deep learning-based artificial vision for grasp classification in myoelectric hands.
TL;DR: A deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis and shows for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.
Journal ArticleDOI
Optobionic vision-a new genetically enhanced light on retinal prosthesis
Patrick Degenaar,Nir Grossman,M. A. Memon,Juan Burrone,Martin D. Dawson,Emmanuel M. Drakakis,Mark A. A. Neil,Konstantin Nikolic +7 more
TL;DR: It is shown that typically 100 mW cm(-2) in instantaneous light intensity on the neuron in order to stimulate action potentials is needed, and how this can be reduced down to safe levels to negate thermal and photochromic damage to the eye.