ABSTRACT
The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.
ABSTRACT
Retinal implants have been developed as a promising way to restore partial vision for the blind. The observation and analysis of neural activities can offer valuable insights for successful prosthetic electrical stimulation. Retinal ganglion cell (RGC) activities have been investigated to provide knowledge on the requirements for electrical stimulation, such as threshold current and the effect of stimulation waveforms. To develop a detailed ‘stimulation strategy’ for faithful delivery of spatiotemporal visual information to the brain, it is essential to examine both the temporal and spatial characteristics of RGC responses, whereas previous studies were mainly focused on one or the other. In this study, we investigate whether the spatiotemporal visual information can be decoded from the RGC network activity evoked by patterned electrical stimulation. Along with a thorough characterization of spatial spreading of stimulation current and temporal information encoding, we demonstrated that multipixel spatiotemporal visual information can be accurately decoded from the population activities of RGCs stimulated by amplitude-modulated pulse trains. We also found that the details of stimulation, such as pulse amplitude range and pulse rate, were crucial for accurate decoding. Overall, the results suggest that useful visual function may be restored by amplitude modulation-based retinal stimulation.
Subject(s)
Brain , Electric Stimulation , Heart Rate , Retinal Ganglion Cells , RetinaldehydeABSTRACT
For successful restoration of visual function by a visual neural prosthesis such as retinal implant, electrical stimulation should evoke neural responses so that the information on visual input is properly represented. A stimulation strategy, which means a method for generating stimulation waveforms based on visual input, should be developed for this purpose. We proposed to use the decoding of visual input from retinal ganglion cell (RGC) responses for the evaluation of stimulus encoding strategy. This is based on the assumption that reliable encoding of visual information in RGC responses is required to enable successful visual perception. The main purpose of this study was to determine the influence of inter-dependence among stimulated RGCs activities on decoding accuracy. Light intensity variations were decoded from multiunit RGC spike trains using an optimal linear filter. More accurate decoding was possible when different types of RGCs were used together as input. Decoding accuracy was enhanced with independently firing RGCs compared to synchronously firing RGCs. This implies that stimulation of independently-firing RGCs and RGCs of different types may be beneficial for visual function restoration by retinal prosthesis.