Tetko I V, Villa A E
Laboratoire de Neuro-heuristique, Institut de Physiologie, Université de Lausanne, Rue du Bugnon 7, CH-1005, Lausanne, Switzerland.
J Neurosci Methods. 2001 Jan 30;105(1):15-24. doi: 10.1016/s0165-0270(00)00337-x.
This study demonstrates the practical application of the pattern grouping algorithm (PGA), presented in the companion paper (Tetko IV, Villa AEP. A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 1. Detection of repeated patterns. J. Neurosci. Methods 2000; accompanying article), to data sets including up to 30 simultaneously recorded spike trains. The analysis of a large network of simulated neurons shows that the incidence of patterns cannot be simply related to an increase in firing rates obtained after Hebbian learning. Patterns that disappeared and reappeared in the thalamus of anesthetized rats when the cerebral cortex was reversibly inactivated suggest that widespread cell assemblies contribute to the generation and propagation of precisely timed activity. In an another experiment multiple spike trains were recorded from the temporal cortex of freely moving rats performing a complex two-choice discrimination task. The presence or absence of particular patterns in the period preceding the cue was associated with changes in reaction time. In conclusion, neuronal network interactions may generate spatiotemporal firing patterns detectable by PGA. We provide evidence of such patterned activity associated with specific animal's behavior, thus suggesting the existence of complex temporal coding schemes in the higher nervous centers of the brain.
本研究展示了配套论文（Tetko IV, Villa AEP. 一种用于分析神经元放电序列时空模式的模式分组算法。1. 重复模式的检测。《神经科学方法杂志》2000年；配套文章）中提出的模式分组算法（PGA）在包含多达30个同时记录的放电序列的数据集上的实际应用。对大型模拟神经元网络的分析表明，模式的发生率不能简单地与赫布学习后获得的放电率增加相关。当大脑皮层可逆性失活时，在麻醉大鼠丘脑消失和重新出现的模式表明，广泛的细胞集合有助于精确计时活动的产生和传播。在另一项实验中，从执行复杂二选一辨别任务的自由活动大鼠的颞叶皮层记录了多个放电序列。提示出现之前特定模式的存在与否与反应时间的变化有关。总之，神经网络相互作用可能产生可被PGA检测到的时空放电模式。我们提供了与特定动物行为相关的这种模式化活动的证据，从而表明大脑高级神经中枢中存在复杂的时间编码方案。
