• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.2
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• pp.132-137
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• 2004

In order to assess electrophysiological responses of fish, a recording of Electroretinogram (ERG) was made on the dark-adapted eyes of anesthetized jack mackerel Trachurus japonicus in the strobe-flash frequency range of 1.7~25 Hz and in the intensity range of 56~415 lx.s. The amplitude change of the ERG is highest at the moment when the strobe light is irradiated and becomes weakest soon after, then gradually increases and becomes stable. The amplitude of the ERG by strobe flash frequencies looked stable tendency after about 12~17 minutes elapsed. During the test duration of 30 minutes, the maximum of amplitude change and stimulation amount over all the tested frequencies was found at 10 Hz. The reduction of the flash intensity caused the decrease in the amplitude and stimulation amount.

• Progress in Medical Physics
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• v.16 no.3
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• pp.148-154
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• 2005

Since the output of retina for visual stimulus is carried by neurons of very diverse functional properties, it is not adequate to use conventional single electrode for recording the retinal action potential. For this purpose, we used newly developed multichannel recording system for monitoring the simultaneous electrical activities of many neurons in a functioning piece of retina. Retinal action potentials are recorded with an extra-cellular planar array of 60 microelectrodes. In studying the collective activity of the ganglion cell population it is essential to recognize basic functional distinctions between individual neurons. Therefore, it is necessary to detect and to classify the action potential of each ganglion cell out of mixed signal. We programmed M-files with MATLAB for this sorting process. This processing is mandatory for further analysis, e.g. poststimulus time histogram (PSTH), auto-correlogram, and cross-correlogram. We established MATLAB based protocol for waveform classification and verified that this approach was effective as an initial spike sorting method.

• Progress in Medical Physics
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• v.17 no.4
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• pp.260-267
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• 2006

A retinal ganglion cell's receptive field is defined as that region on the retinal surface In which a light stimulus will produce a response. A retinal ganglion cell peers out at a small patch of the visual scene through its receptive field and encodes local features with action potentials that pass through the optic nerve to higher centers. Therefore, defining the receptive field of a retinal ganglion cell is essential to understand the electrical characteristics of a ganglion cell. Distribution of receptive fields over retinal surface provides us an Insight how the retinal ganglion cell processes the visual scene. In this paper, we provide the details how to reconstruct the receptive field of a retinal ganglion cell. We recorded the ganglion cell's action potential with multielectrode array when the random checkerboard stimulus was applied. After classifying the retinal waveform Into ON-cell, OFF-cell, ON/OFF-cell, we reconstructed the receptive field of retinal ganglion cell with Matlab. Here, we show the receptive fields of ON-cell and OFF-cell.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.611-615
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• 2004

A neural prostheses can be designed to permit stimulation of specific sites in the nervous system to restore their functions, lost due to disease or trauma. This study focuses on the feasibility of optoelecronic stimulation into nervous system. Optoelectronic stimulation supplies, power and signal into the implanted optical detector inside the body by optics. It can be effective strategy especially on the retinal prosthesis, because it enables the non-invasive connection between the external source and internal detector through natural optical window 'eye'. Therefore, we designed an effective neural stimulating setup by optically based stimulation. Stimulating on the sciatic nerve of a rat with proper depth probe through optical stimulation needs higher ratio of current spreading through the neural surface, because of high impedance of neural interface. To increase the insertion current spreading into the neuron, we used a parallel low resistance compared to load resistance organic interface and calculated the optimized outer parallel resistance for maximum insertion current with the assumption of limited current by photodiode. Optimized outer parallel resistance was at a range of 500Ω-700Ω and a current was at a level between 580uA and 650uA. Stimulating current efficiency from initial photodiode induced current was between 47.5 and 59.7%. Various amplitude and frequency of the optical stimulation on the sciatic nerve showed the reliable visual tremble, and the action potential was also recorded near the stimulating area. These result demonstrate that optoelectronic stimulation with no bias can be applied to the retinal prosthesis and other neuroprosthetic area.