Abstract:
The inferior colliculus (IC) is a critical computational hub in the central auditory pathway. From its position in the midbrain, the IC receives nearly all the ascending output from the lower auditory brainstem and provides the main source of auditory information to the thalamocortical system. In addition to being a crossroads for auditory circuits, the IC is rich with local circuits and contains more than five times as many neurons as the nuclei of the lower auditory brainstem combined. These results hint at the enormous computational power of the IC, and indeed, systems-level studies have identified numerous important transformations in sound coding that occur in the IC. However, despite decades of effort, the cellular mechanisms underlying IC computations and how these computations change following hearing loss have remained largely impenetrable. In this review, we argue that this challenge persists due to the surprisingly difficult problem of identifying the neuron types and circuit motifs that comprise the IC. After summarizing the extensive evidence pointing to a diversity of neuron types in the IC, we highlight the successes of recent efforts to parse this complexity using molecular markers to define neuron types. We conclude by arguing that the discovery of molecularly identifiable neuron types ushers in a new era for IC research marked by molecularly targeted recordings and manipulations. We propose that the ability to reproducibly investigate IC circuits at the neuronal level will lead to rapid advances in understanding the fundamental mechanisms driving IC computations and how these mechanisms shift following hearing loss.
摘要:
下丘(IC)是中枢听觉通路中的关键计算枢纽。从它在中脑的位置来看,IC接收来自下听觉脑干的几乎所有上升输出,并为丘脑皮质系统提供听觉信息的主要来源。除了是听觉电路的十字路口,IC具有丰富的局部电路,包含的神经元是下听觉脑干核的五倍多。这些结果暗示了IC的巨大计算能力,事实上,系统级研究已经确定了在IC中发生的声音编码中的许多重要转换。然而,尽管几十年的努力,IC计算的细胞机制以及这些计算在听力损失后的变化在很大程度上仍然难以理解。在这次审查中,我们认为,由于识别包含IC的神经元类型和电路基序的令人惊讶的困难问题,这一挑战仍然存在。在总结了指向IC中神经元类型多样性的大量证据之后,我们强调了最近使用分子标记来定义神经元类型来解析这种复杂性的努力的成功。我们得出结论,认为分子可识别的神经元类型的发现开启了以分子靶向记录和操作为标志的IC研究的新时代。我们建议,在神经元水平上可重复研究IC电路的能力将导致在理解驱动IC计算的基本机制以及这些机制在听力损失后如何变化方面的快速发展。