Spike Correlations in a Songbird Agree with a Simple Markov Population Model

Spike Correlations in a Songbird Agree with a Simple Markov Population Model
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鸣禽的尖峰相关性与简单的马尔可夫种群模型一致

DOI:
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发表时间:
2007
期刊:
PLoS Comput. Biol.
影响因子:
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通讯作者:
Richard Hans Robert Hahnloser
Richard Hans Robert Hahnloser
中科院分区:
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文献类型:
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作者:
Andrea P. Weber;Richard Hans Robert Hahnloser

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单细胞水平和群体水平的神经活动之间的关系对于理解神经密码至关重要。在许多感觉系统中,大细胞群中的集体行为可以用成对尖峰相关来描述。在这里,我们测试了在鸣禽高度专业化的前运动系统中,成对尖峰相关性本身是否可以被视为潜在随机过程的简单推论。我们使用独立于详细的单个神经元特性的高级种群模型来测试斑马雀运动通路中连通性和网络动力学的假设。我们假设在歌唱过程中,神经群的活动沿着一组有限的状态进化,而在睡眠过程中,神经群的活动在歌唱状态和单一的休息状态之间随机地来回切换。单独的尖峰序列是通过与每一种群体状态相关联而产生的一种特定的放电模式,例如爆裂放电或强直放电。通过对一个或两个简单控制参数的全面修改,马尔可夫模型能够再现观察到的放电统计数据和不同神经元类型和行为状态下的峰值相关性。我们的研究结果表明,歌唱和睡眠相关的放电模式在短时间尺度上是相同的,并且是由一个独特的潜在主题的随机抽样产生的。我们的种群模型的效率也可以应用于其他神经系统,在这些系统中,种群假设可以通过小神经元组的记录进行测试。
The relationships between neural activity at the single-cell and the population levels are of central importance for understanding neural codes. In many sensory systems, collective behaviors in large cell groups can be described by pairwise spike correlations. Here, we test whether in a highly specialized premotor system of songbirds, pairwise spike correlations themselves can be seen as a simple corollary of an underlying random process. We test hypotheses on connectivity and network dynamics in the motor pathway of zebra finches using a high-level population model that is independent of detailed single-neuron properties. We assume that neural population activity evolves along a finite set of states during singing, and that during sleep population activity randomly switches back and forth between song states and a single resting state. Individual spike trains are generated by associating with each of the population states a particular firing mode, such as bursting or tonic firing. With an overall modification of one or two simple control parameters, the Markov model is able to reproduce observed firing statistics and spike correlations in different neuron types and behavioral states. Our results suggest that song- and sleep-related firing patterns are identical on short time scales and result from random sampling of a unique underlying theme. The efficiency of our population model may apply also to other neural systems in which population hypotheses can be tested on recordings from small neuron groups.
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