Complex spike patterns in olfactory bulb neuronal networks
Complex spike patterns in olfactory bulb neuronal networks
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DOI：
10.1016/j.jneumeth.2014.09.016
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发表时间：
2015-01
影响因子：
3
通讯作者：
A. Nicol;A. Segonds-Pichon;M. Magnússon
中科院分区：
文献类型：
--
作者：
A. Nicol;A. Segonds-Pichon;M. Magnússon
背景T-模式分析是一种为检测非随机重复的分层和多序实时序列模式（T-模式）而开发的程序。新方法我们询问是否可以从跨嗅球（OB）二尖瓣细胞层的许多神经元同时采样的细胞外活动中提取这种动作电位（尖峰）模式。在 6 小时的记录时间内或在动物生理条件允许的时间内持续从氨基甲酸乙酯麻醉的大鼠中采集尖峰样品。记录呼吸以标记吸气和呼气峰值。结果最多~20 个元素的复杂 T 模式被识别，其功能连接通常跨越阵列的整个范围。这些序列中有相当一部分包含呼吸。与现有方法相比，与 synfire 的序列检测相比，在我们的真实数据中检测到的序列的发生率比通过改组或保留每个尖峰序列的间隔结构的替代程序进行随机化时在相同数据中检测到的序列的发生率要大得多，因此更加保守。此外，当记录在完整记录会话完成之前终止时，真实和随机数据中的相对模式检测是生理状况的有力指标——在导致制剂变得生理不稳定的记录中，真实数据中检测到的模式数量接近随机数据中的数量。结论我们得出结论，此类序列是所研究的神经系统的重要生理特性，并表明它们可能构成编码感觉的基础 信息。
BackgroundT-pattern analysis is a procedure developed for detecting non-randomly recurring hierarchical and multiordinal real-time sequential patterns (T-patterns).New methodWe have inquired whether such patterns of action potentials (spikes) can be extracted from extracellular activity sampled simultaneously from many neurons across the mitral cell layer of the olfactory bulb (OB). Spikes were sampled from urethane-anaesthetized rats over a 6 h recording session, or a period lasting as long as permitted by the physiological condition of the animal. Breathing was recorded to mark peak inhalation and exhalation.ResultsComplex T-patterns of up to ∼20 elements were identified with functional connections often spanning the full extent of the array. A considerable proportion of these sequences incorporated breathing.Comparison with existing methodsIn contrast to sequence detection by synfire, the incidence of sequences detected in our real data is very much greater than in the same data when randomized either by shuffling, or an alternative procedure preserving the interval structure of each spike train, and so more conservative. Further, when recordings were terminated before completion of the full recording session, the relative pattern detection in real and randomized data was a strong indicator of physiological condition—in recordings leading up to the preparation becoming physiologically unstable, the number of patterns detected in real data approached that in the randomized data.ConclusionsWe conclude that such sequences are an important physiological property of the neural system studied, and suggest that they may form a basis for encoding sensory information.