A computational model of orientation-dependent activation of retinal ganglion cells

Timothy Esler; Anthony N Burkitt; David B Grayden; Robert R Kerr; Bahman Tahayori; Hamish Meffin

Conference Proceedings

A computational model of orientation-dependent activation of retinal ganglion cells

Timothy Esler, Anthony N Burkitt, David B Grayden, Robert R Kerr, Bahman Tahayori, Hamish Meffin, J Patton (ed.), R Barbieri (ed.), J Ji (ed.), E Jabbari (ed.), S Dokos (ed.), R Mukkamala (ed.), D Guiraud (ed.), E Jovanov (ed.), Y Dhaher (ed.), D Panescu (ed.), M Vangils (ed.), B Wheeler (ed.), AP Dhawan (ed.)

2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | IEEE | Published : 2016

DOI: 10.1109/EMBC.2016.7591959

Abstract

Currently, a challenge in electrical stimulation for epiretinal prostheses is the avoidance of stimulation of axons of passage in the nerve fiber layer that originate from distant regions of the ganglion cell layer. A computational model of extracellular stimulation that captures the effect of neurite orientation in anisotropic tissue is developed using a modified version of the standard volume conductor model, known as the cellular composite model, embedded in a four layer model of the retina. Simulations are conducted to investigate the interaction of neural tissue orientation, electrode placement, and stimulation pulse duration and amplitude. Using appropriate multiple electrode configura..

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University of Melbourne Researchers

Hamish Meffin Author Biomedical Engineering

David Grayden Author Biomedical Engineering

Bahman Tahayori Author Chemical and Biomedical Engineering

Anthony Burkitt Author Biomedical Engineering

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Grants

Awarded by Australian Research Council's Discovery Projects funding scheme

Awarded by Victorian Life Sciences Computation Initiative (VLSCI) on its Peak Computing Facility at the University of Melbourne

Funding Acknowledgements

The authors acknowledge support under the Australian Research Council's Discovery Projects funding scheme (project number DP140104533). This research was supported by Victorian Life Sciences Computation Initiative (VLSCI) grant number VR0138 on its Peak Computing Facility at the University of Melbourne, and initiative of the Victorian Government.