Quantitative Analysis Of Neuronal Network Cultured On Microelectrode Arrays

With the further research on central nervous system and peripheral nervous systems,it is becoming more and more important to develop a research platform and/or a new method by combining physiology to information technology.The microelectrode technique has special advantages in analyzing the properties of neuronal network,especially sampling data in a tiny space,therefore becoming a new method for detecting signals from neuronal networks,which is one of the most important fields in research on nervous system.The developed method thus was utilized to detect the states of cultured neuronal networks before and after different stimulus by microelectrode arrays(MEA)in this work.The research on neurons could be majorly divided into simulation and physiology experiments,also known as neural networks and neuronal networks.In physiology experiments,the mean of spike rates is usually used to analyze the condition of neuronal networks while in simulation,the inner structure of network is focused.It is possible to do a further analysis of cultured neuronal networks by using physiology experiments while referring to structure modules in simulation.In this paper,neurons were cultured on MEA chips and the signal was detected by microelectrodes of MEA chips.Based on physiology experiments,the patterns of spontaneous activities and evoked activities were analyzed to evaluate process of growth and stimulus-response of neurons.The patterns of spontaneous activities were further analyzed by using spike rate and correlation coefficient.In spontaneous activities,spike rate fluctuated around a base line and the correlation coefficient revealed the fact that the distance does not have significant influence on synchronization between different parts in neuronal networks.Electrical stimulus with different amplitudes and in different areas were applied to neuronal networks,and evoked activities were analyzed accordingly.In evoked activities,first response after stimulus was used as a vital feature wich shows that the neuronal networks would generate a fast response in some areas.More areas would have the fast response with the increase of amplitudes,while the time of fast response would not be faster and the response structure would not change.It is also showed that stimulus done in different areas is able to induce a variation of distribution of areas having fast response,as well as the duration of the fast response and the structure of stimulus-response.After the long-term stimulus,the spike rate would be increased and spike weight of neuronal networks would be slightly changed.According to the experimental finding,,the obtained properties of spontaneous activities and evoked activities are effectively analyzed and could be used to further decoding neuronal signals and understating the learning and training of the netwo rk by using the electrical signal of neuronal networks.