Witharana W K L, Cardiff J, Chawla M K, Xie J Y, Alme C B, Eckert M, Lapointe V, Demchuk A, Maurer A P, Trivedi V, Sutherland R J, Guzowski J F, Barnes C A, McNaughton B L
Canadian Centre for Behavioural Neuroscience, University of Lethbridge, T1K 3M4.
Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, Arizona.
Hippocampus. 2016 Oct;26(10):1328-44. doi: 10.1002/hipo.22609. Epub 2016 Jun 24.
The mechanisms governing how the hippocampus selects neurons to exhibit place fields are not well understood. A default assumption in some previous studies was the uniform random draw with replacement (URDWR) model, which, theoretically, maximizes spatial "pattern separation", and predicts a Poisson distribution of the numbers of place fields expressed by a given cell per unit area. The actual distribution of mean firing rates exhibited by a population of hippocampal neurons, however, is approximately exponential or log-normal in a given environment and these rates are somewhat correlated across multiple places, at least under some conditions. The advantage of neural activity-dependent immediate-early gene (IEG) analysis, as a proxy for electrophysiological recording, is the ability to obtain much larger samples of cells, even those whose activity is so sparse that they are overlooked in recording studies. Thus, a more accurate representation of the activation statistics can potentially be achieved. Some previous IEG studies that examined behavior-driven IEG expression in CA1 appear to support URDWR. There was, however, in some of the same studies, an under-recruitment of dentate gyrus granule cells, indicating a highly skewed excitability distribution, which is inconsistent with URDWR. Although it was suggested that this skewness might be related to increased excitability of recently generated granule cells, we show here that CA1, CA3, and subiculum also exhibit cumulative under-recruitment of neurons. Thus, a highly skewed excitability distribution is a general principle common to all major hippocampal subfields. Finally, a more detailed analysis of the frequency distributions of IEG intranuclear transcription foci suggests that a large fraction of hippocampal neurons is virtually silent, even during sleep. Whether the skewing of the excitability distribution is cell-intrinsic or a network phenomenon, and the degree to which this excitability is fixed or possibly time-varying are open questions for future studies. © 2016 Wiley Periodicals, Inc.
海马体如何选择神经元来展现位置野的机制尚未完全明确。先前一些研究中的一个默认假设是有放回的均匀随机抽取（URDWR）模型，从理论上讲，该模型能使空间“模式分离”最大化，并预测给定细胞在单位面积内表达的位置野数量呈泊松分布。然而，在给定环境中，海马神经元群体表现出的平均放电率的实际分布大致呈指数分布或对数正态分布，并且这些放电率在多个位置之间存在一定程度的相关性，至少在某些条件下是这样。神经活动依赖的即早基因（IEG）分析作为电生理记录的替代方法，其优势在于能够获取更多的细胞样本，甚至包括那些活动极为稀疏以至于在记录研究中被忽略的细胞。因此，有可能实现对激活统计数据更准确的描述。先前一些研究即早基因在CA1区的行为驱动性表达似乎支持URDWR模型。然而，在其中一些相同的研究中，齿状回颗粒细胞的募集不足，这表明兴奋性分布高度偏态，这与URDWR模型不一致。尽管有人认为这种偏态可能与新生成颗粒细胞兴奋性增加有关，但我们在此表明，CA1区、CA3区和下托也存在神经元募集不足的累积现象。因此，高度偏态的兴奋性分布是所有主要海马亚区共有的普遍原则。最后，对即早基因核内转录灶频率分布的更详细分析表明，即使在睡眠期间，很大一部分海马神经元实际上也是沉默的。兴奋性分布的偏态是细胞内在的还是网络现象，以及这种兴奋性在多大程度上是固定的或可能随时间变化，这些都是未来研究有待解决的问题。© 2016威利期刊公司
