TY - GEN
T1 - Computational models and tools for developing sophisticated stimulation strategies for retinal neuroprostheses
AU - Guo, Tianruo
AU - Tsai, David
AU - Muralidharan, Madhuvanthi
AU - Li, Mingli
AU - Suaning, Gregg J.
AU - Morley, John W.
AU - Dokos, Socrates
AU - Lovell, Nigel H.
PY - 2018
Y1 - 2018
N2 - ![CDATA[Improvements to the efficacy of retinal neuroprostheses can be achieved by developing more sophisticated neural stimulation strategies to enable selective or preferential activation of specific retinal ganglion cells (RGCs). Computational models are particularly well suited for these investigations. The electric field can be accurately described by mathematical formalisms, and the population-based neural responses to the electrical stimulation can be investigated at resolutions well beyond those achievable by current state-of-the-art biological techniques. In this study, we used a biophysically-and morphologically-detailed RGC model to explore the ability of high frequency electrical stimulation (HFS) to preferentially activate ON and OFF RGC subtypes, the two major information pathways of the retina. The performance of a wide range of electrical stimulation amplitudes (0 100 μ A and frequencies (1 - 10 kHz) on functionally-distinct RGC responses were evaluated. We found that ON RGCs could be preferentially activated at relatively higher stimulation amplitudes ( > 50 μ A and frequencies ( >2 kHz) while OFF RGCs were activated by lower stimulation amplitudes (10 to 50 {μ A across all tested frequencies. These stimuli also show great promise in eliciting RGC responses that parallel RGC encoding: one RGC type exhibited an increase in spiking activity during electrical stimulation whilst another exhibited decreased spiking activity, given the same stimulation parameters.]]
AB - ![CDATA[Improvements to the efficacy of retinal neuroprostheses can be achieved by developing more sophisticated neural stimulation strategies to enable selective or preferential activation of specific retinal ganglion cells (RGCs). Computational models are particularly well suited for these investigations. The electric field can be accurately described by mathematical formalisms, and the population-based neural responses to the electrical stimulation can be investigated at resolutions well beyond those achievable by current state-of-the-art biological techniques. In this study, we used a biophysically-and morphologically-detailed RGC model to explore the ability of high frequency electrical stimulation (HFS) to preferentially activate ON and OFF RGC subtypes, the two major information pathways of the retina. The performance of a wide range of electrical stimulation amplitudes (0 100 μ A and frequencies (1 - 10 kHz) on functionally-distinct RGC responses were evaluated. We found that ON RGCs could be preferentially activated at relatively higher stimulation amplitudes ( > 50 μ A and frequencies ( >2 kHz) while OFF RGCs were activated by lower stimulation amplitudes (10 to 50 {μ A across all tested frequencies. These stimuli also show great promise in eliciting RGC responses that parallel RGC encoding: one RGC type exhibited an increase in spiking activity during electrical stimulation whilst another exhibited decreased spiking activity, given the same stimulation parameters.]]
UR - https://hdl.handle.net/1959.7/uws:67468
U2 - 10.1109/EMBC.2018.8512748
DO - 10.1109/EMBC.2018.8512748
M3 - Conference Paper
SN - 9781538636466
SP - 2248
EP - 2251
BT - Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '18), Honolulu, Hawaii, USA, 18-21 July 2018
PB - IEEE
T2 - IEEE Engineering in Medicine and Biology Society. Annual Conference
Y2 - 17 July 2018
ER -