Department of Physiology, McGill University, Montreal, Quebec, Canada.
J Neurophysiol. 2011 Dec;106(6):3102-18. doi: 10.1152/jn.00588.2011. Epub 2011 Sep 21.
While peripheral sensory neurons respond to natural stimuli with a broad range of spatiotemporal frequencies, central neurons instead respond sparsely to specific features in general. The nonlinear transformations leading to this emergent selectivity are not well understood. Here we characterized how the neural representation of stimuli changes across successive brain areas, using the electrosensory system of weakly electric fish as a model system. We found that midbrain torus semicircularis (TS) neurons were on average more selective in their responses than hindbrain electrosensory lateral line lobe (ELL) neurons. Further analysis revealed two categories of TS neurons: dense coding TS neurons that were ELL-like and sparse coding TS neurons that displayed selective responses. These neurons in general responded to preferred stimuli with few spikes and were mostly silent for other stimuli. We further investigated whether information about stimulus attributes was contained in the activities of ELL and TS neurons. To do so, we used a spike train metric to quantify how well stimuli could be discriminated based on spiking responses. We found that sparse coding TS neurons performed poorly even when their activities were combined compared with ELL and dense coding TS neurons. In contrast, combining the activities of as few as 12 dense coding TS neurons could lead to optimal discrimination. On the other hand, sparse coding TS neurons were better detectors of whether their preferred stimulus occurred compared with either dense coding TS or ELL neurons. Our results therefore suggest that the TS implements parallel detection and estimation of sensory input.
虽然周围感觉神经元可以对自然刺激以广泛的时空频率做出反应，但中枢神经元通常对特定特征的反应稀疏。导致这种涌现选择性的非线性转换尚不清楚。在这里，我们使用弱电鱼的电感觉系统作为模型系统，描述了刺激的神经表示如何在连续的脑区中发生变化。我们发现，中脑半规管（TS）神经元的反应平均比后脑电感觉侧线叶（ELL）神经元更具选择性。进一步的分析显示了两类 TS 神经元：与 ELL 相似的密集编码 TS 神经元和显示选择性反应的稀疏编码 TS 神经元。这些神经元通常对优选刺激的反应只有少数几个尖峰，而对其他刺激则大多处于沉默状态。我们进一步研究了刺激属性的信息是否包含在 ELL 和 TS 神经元的活动中。为此，我们使用尖峰序列度量来量化根据尖峰反应可以多好地区分刺激。我们发现，即使将其活动结合起来，稀疏编码 TS 神经元的性能也很差，与 ELL 和密集编码 TS 神经元相比。相比之下，仅将 12 个密集编码 TS 神经元的活动组合起来，就可以实现最佳的区分。另一方面，与密集编码 TS 或 ELL 神经元相比，稀疏编码 TS 神经元更能检测到它们的首选刺激是否发生。因此，我们的结果表明，TS 实现了对感觉输入的并行检测和估计。
