Sun Wensheng, Marongelli Ellisha N, Watkins Paul V, Barbour Dennis L
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri.
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri
J Neurophysiol. 2017 Oct 1;118(4):2024-2033. doi: 10.1152/jn.00670.2016. Epub 2017 Jul 12.
Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons. Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts.
在整个中枢听觉系统中,都观察到了对特定声级有良好反应的神经元,并且在更高的处理区域中,这类神经元越来越常见。关于这些声级调谐或非单调神经元的作用,有一种理论认为它们对声音进行声级不变编码。为了研究这一理论,我们通过提取真实初级听觉皮层(A1)神经元的反应,模拟了各种神经元亚群,并考察了它们在形成不同声级表征时的表现。单纯的非单调亚群并不能提供最佳的声级不变解码;相反,单调神经元和非单调神经元的混合群体提供了最准确的解码。对于声级保真度解码,在非单调神经元占比很高之前,其加入会略微提高或不会改变解码精度。这些结果表明,非单调神经元起到的编码作用是对单调神经元的补充,而非替代。具有非单调速率-声级函数的神经元是中枢听觉系统所特有的。有人提出,这些声级调谐神经元能够解释跨声级的不变声音感知。通过基于真实神经元反应的系统模拟,本研究表明,当同时包含单调神经元和非单调神经元时,神经元群体能够实现最佳的声音编码。结果表明,非单调神经元并非独立发挥作用,而是在不同的声音编码情境中补充单调神经元的功能。