Determining the cellular content of the nervous system in terms of cell types and the rules of their connectivity represents a fundamental challenge to the neurosciences. The recent advent of high-throughput techniques, such as single-cell RNA-sequencing has allowed for greater resolution in the identification of cell types and/or states. Although most of the current neuronal classification schemes comprise discrete clusters, several recent studies have suggested that, perhaps especially, within the striatum, neuronal populations exist in continua, with regards to both their molecular and electrophysiological properties. Whether these continua are stable properties, established during development, or if they reflect acute differences in activity-dependent regulation of critical genes is currently unknown. We set out to determine whether gradient-like molecular differences in the recently described Pthlh-expressing inhibitory interneuron population, which contains the Pvalb-expressing cells, correlate with differences in morphological and connectivity properties. We show that morphology and long-range inputs correlate with a spatially organized molecular and electrophysiological gradient of Pthlh-interneurons, suggesting that the processing of different types of information (by distinct anatomical striatal regions) has different computational requirements.

根据细胞类型及其连接规则确定神经系统的细胞含量是对神经科学的一项基本挑战。最近出现的高通量技术，例如单细胞 RNA 测序，使得在识别细胞类型和/或状态方面具有更高的分辨率。尽管当前的大多数神经元分类方案都包含离散的簇，但最近的一些研究表明，也许特别是在纹状体内，神经元群存在于连续体中，就其分子和电生理学特性而言。这些连续体是否是在发育过程中建立的稳定特性，或者它们是否反映了关键基因的活性依赖性调节的严重差异，目前尚不清楚。表达 Pthlh 的抑制性中间神经元群，包含表达 Pvalb 的细胞，与形态和连接特性的差异相关。我们表明形态学和远程输入与 Pthlh 中间神经元的空间组织分子和电生理梯度相关，表明不同类型信息的处理（通过不同的解剖纹状体区域）具有不同的计算要求。