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http://dx.doi.org/10.9718/JBER.2007.28.2.212

Estimation of Visual Stimulus Intensity From Retinal Ganglion Cell Spike Trains Using Optimal Linear Filter  

Ryu, Sang-Baek (Department of Biomedical Engineering, College of Health Science and Yonsei Medical Engineering Institute, Yonsei University)
Kim, Doo-Hee (Department of Biomedical Engineering, College of Health Science and Yonsei Medical Engineering Institute, Yonsei University)
Ye, Jang-Hee (Department of Physiology, Chungbuk National University Medical School)
Kim, Kyung-Hwan (Department of Biomedical Engineering, College of Health Science and Yonsei Medical Engineering Institute, Yonsei University)
Goo, Yong-Sook (Department of Physiology, Chungbuk National University Medical School)
Publication Information
Journal of Biomedical Engineering Research / v.28, no.2, 2007 , pp. 212-217 More about this Journal
Abstract
As a preliminary study for the development of electrical stimulation strategy of artificial retina, we set up a method fur the reconstruction of input intensity variation from retinal ganglion cell(RGC) responses. In order to estimate light intensity variation, we used an optimal linear filter trained from given stimulus intensity variation and multiple single unit spike trains from RGCs. By applying ON/OFF stimulation(ON duration: 2 sec, OFF duration: 5 sec) repetitively, we identified three functional types of ganglion cells according to when they respond to the ON/OFF stimulus actively: ON cell, OFF cell, and ON-OFF cell. Experiments were also performed using a Gaussian random stimulus and a binary random stimulus. The input intensity was updated once every 90 msec(i. e. 11 Hz) to present the stimulus. The result of reconstructing 11 Hz Gaussian and binary random stimulus was not satisfactory and showed low correlation between the original and reconstructed stimulus. In the case of ON/OFF stimulus in which temporal variation is slow, successful reconstruction was achieved and the correlation coefficient was as high as 0.8.
Keywords
artificial retina; visual prosthesis; optimal linear filter; spike train decoding; retinal ganglion cell;
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