Automatic System For Identification And Analysis Of Burst

With the development of neural informatics, the research about neurons discharge mode is also in constant depth. Neurons produce many types of electrical spike activity. The neurons activity may be periodic, or clustered in bursts—periods of time with a high spike rate separated by other periods with a much lower spike rate. The patterns of electrical activity reflect various arrangement sequence of the neuron action potential in terms of time, contain a wealth of information and will substantially change with the alternation of the living environment of the neurons. Therefore, it is necessary to analyze the information contained in various types of burst discharges.However, there are some difficulties in the analyses of the burst discharges.1. Since it takes quite some time to record the neuron electrical spikes during the electrophysiological experiment, a huge amount of the interfering signals may be produced which are from the environment of the biotic experimental system and the organism itself. Thus it is very difficult to extract the bursts from the piles of data.2. There are different values of interspike intervals (ISI) in different types of bursts, which make it difficult to use an aptotic ISI value to extract bursts and may bring on inaccurate analysis of bursts.3. While extracellular discharge recordings were made, there were different amplitude spikes occurring. Here, spikes with big amplitude value were defined as the dominant wave and spikes with small amplitude value as the secondary wave. The dominant waves and the secondary waves overlapped and mixed with each other, therefore it is difficult to extract, separate and analyze the two types of waves.In order to solve these problems occurred in extracting and analyzing neuron electrical spikes and bursts, we designed an automatic system for extracting electrical bursts. 1)Analysis of the mainstream electrophysiology laboratory equipment advantages, establishes a new solution to extracting and analyzing the neuron electrical spikes and bursts. 2) Based on this solution, we design the circuit to extracting neuron electrical spikes and bursts, and design the software to analyzing them. 3) Designed an electrophysiological experiment to test this system performance.The article mainly divided into five parts. The first part is introduction the advantages and defects of the mainstream experimental equipments. Make a comparison between the automatic system for identification and analysis of bursts and such experimental equipments. Secondly, introduce the composition of the hardware equipment and the filtering results of the spike magnifying circuit. Thirdly, introduce the software design logical and the new algorithm to analysis bursts. The fourth, designed an electrophysiological experiment to test this system performance. In the last part, we show two patents about this system. The one is named automatic system for extracting electrical bursts, another one is named battery monitoring and real-time charging system in portable bio-functional experimental devices.The system consists of neuron discharge collecting unit, neuron discharge processing unit, battery monitoring, real-time charging unit and bursts processing software. The system can identify the burst discharge from the neuron discharge without any omission and make statistical analysis. By using this device, the electrophysiological experiment that the spontaneous and evoked discharges of wide dynamic range neurons in hippocampal formation neurons were recorded was smoothly completed. The result of statistical analysis indicated that the device can give the corresponding interspike interval aimed at various types of burst discharges and respectively identify the burst discharges in the different amplitude spikes, which provide a tool for further research on the biosensor and the neural communication.