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Cooperative population coding facilitates efficient sound-source separability by adaptation to input statistics

机译:人口协作编码通过适应输入统计数据,促进了有效的声源可分离性

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Our sensory environment changes constantly. Accordingly, neural systems continually adapt to the concurrent stimulus statistics to remain sensitive over a wide range of conditions. Such dynamic range adaptation (DRA) is assumed to increase both the effectiveness of the neuronal code and perceptual sensitivity. However, direct demonstrations of DRA-based efficient neuronal processing that also produces perceptual benefits are lacking. Here, we investigated the impact of DRA on spatial coding in the rodent brain and the perception of human listeners. Complex spatial stimulation with dynamically changing source locations elicited prominent DRA already on the initial spatial processing stage, the Lateral Superior Olive (LSO) of gerbils. Surprisingly, on the level of individual neurons, DRA diminished spatial tuning because of large response variability across trials. However, when considering single-trial population averages of multiple neurons, DRA enhanced the coding efficiency specifically for the concurrently most probable source locations. Intrinsic LSO population imaging of energy consumption combined with pharmacology revealed that a slow-acting LSO gain-control mechanism distributes activity across a group of neurons during DRA, thereby enhancing population coding efficiency. Strikingly, such “efficient cooperative coding” also improved neuronal source separability specifically for the locations that were most likely to occur. These location-specific enhancements in neuronal coding were paralleled by human listeners exhibiting a selective improvement in spatial resolution. We conclude that, contrary to canonical models of sensory encoding, the primary motive of early spatial processing is efficiency optimization of neural populations for enhanced source separability in the concurrent environment. The efficient coding hypothesis suggests that sensory processing adapts to the stimulus statistics to maximize information while minimizing energetic costs. This study finds that an auditory spatial processing circuit distributes activity across neurons to enhance processing efficiency, focally improving spatial resolution both in neurons and in human listeners.
机译:我们的感官环境不断变化。因此,神经系统不断适应并发刺激统计,以在各种条件下保持敏感。假定这种动态范围适应(DRA)可以增加神经元代码的有效性和感知灵敏度。但是,缺乏直接的基于DRA的有效神经元加工的证明,该加工也产生了感性的好处。在这里,我们研究了DRA对啮齿动物大脑中空间编码和人类听众感知的影响。具有动态变化源位置的复杂空间刺激已经在初始空间处理阶段即沙土鼠的上侧橄榄(LSO)上引起了杰出的DRA。令人惊讶的是,在各个神经元的水平上,DRA减少了空间调整,因为各个试验之间的反应差异很大。但是,当考虑多个神经元的单次试验平均值时,DRA特别针对同时存在的最可能的源位置提高了编码效率。 LSO能量消耗的内在成像与药理学相结合显示,DRA期间,缓慢起作用的LSO增益控制机制可在一组神经元之间分布活性,从而提高了群体编码效率。令人惊讶的是,这种“有效的协作编码”还改善了神经源的可分离性,特别是针对最可能发生的位置。神经元编码中的这些特定于位置的增强与人类听众并行显示了空间分辨率的选择性提高。我们得出结论,与感觉编码的典范模型相反,早期空间处理的主要动机是对神经种群进行效率优化,以在并行环境中增强源可分离性。有效的编码假设表明,感觉处理适应刺激统计信息以最大化信息,同时最小化精力成本。这项研究发现,听觉空间处理电路可以在神经元之间分布活动,从而提高处理效率,并集中改善神经元和人类听众的空间分辨率。

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