%0 Journal Article
%T IMPROVED SELF-ADAPTIVE ALGORITHM FOR BURST DETECTION BASED ON THE MAXIMUM INTERSPIKE INTERVAL<br>基于最大锋电位间隔的爆发检测自适应算法
%A CHEN Lin
%A LIN Yun-sheng
%A CHEN Chuan-ping
%A LI Xiang-ning
%A ZHOU Wei
%A ZENG Shao-qun
%A LUO Qing-ming
%A <br>陈
%A 琳
%A 林云生
%A 
%A 陈传平
%A 
%A 李向宁
%A 
%A 周
%A 炜
%A 
%A 曾绍群
%A 
%A 骆清铭
%J 生物物理学报
%D 2006
%I 
%X Bursts are observed in various neuronal types of mammalian central nervous system and in organotypic slice cultures or in various cultures of neural networks in vitro, which are regarded as an important feature of spatial-temporal spike patterns. A sequence of action potentials (spike train) often has high frequency spike episodes that are generally called bursts. The complexity of bursts on timescale brings out many difficulties for identification and detection. Bursts are detected by self-adaptive algorithm when the inter-burst intervals (inter-spike intervals (ISIs) between bursts) exceed the intra-burst periods (the sum of ISIs within a burst). To improve the burst-detection self-adaptive algorithm, the maximum interspike interval parameter during the bursting is considered as a constraint condition to identify burst. The results indicated that the improved algorithm efficiently avoided pretermissions and mistakes for burst-detection. It can exactly detect the burst activities of neuron and identify the parameters such as number of bursts, the burst duration. About 93.8% of the average validity for the burst detection was achieved by using the improved method. Comparing with the self-adaptive algorithm, the average validity increased 35.3%.
%K Burst
%K Interspike intervals(ISIs)
%K Burst duration
%K Interburst intervals(IBIs)
%K Self-adaptive algorithm<br>爆发
%K 锋电位间隔
%K 爆发持续时间
%K 爆发间隔
%K 自适应算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=E0C9D9BBED813D6674AC13E942EAC86D&aid=C0C5D1F2835F76AB&yid=37904DC365DD7266&vid=BC12EA701C895178&iid=E158A972A605785F&sid=E42CAFB11D4BE21A&eid=119B6C0AA09DE6B9&journal_id=1000-6737&journal_name=生物物理学报&referenced_num=4&reference_num=11