Laboratoire de Neurosciences Cognitives, École Normale Supérieure, Paris, France.
Champalimaud Centre for the Unknown, Lisbon, Portugal.
Nat Neurosci. 2016 Mar;19(3):375-82. doi: 10.1038/nn.4243.
Recent years have seen a growing interest in inhibitory interneurons and their circuits. A striking property of cortical inhibition is how tightly it balances excitation. Inhibitory currents not only match excitatory currents on average, but track them on a millisecond time scale, whether they are caused by external stimuli or spontaneous fluctuations. We review, together with experimental evidence, recent theoretical approaches that investigate the advantages of such tight balance for coding and computation. These studies suggest a possible revision of the dominant view that neurons represent information with firing rates corrupted by Poisson noise. Instead, tight excitatory/inhibitory balance may be a signature of a highly cooperative code, orders of magnitude more precise than a Poisson rate code. Moreover, tight balance may provide a template that allows cortical neurons to construct high-dimensional population codes and learn complex functions of their inputs.
近年来，人们对抑制性中间神经元及其回路越来越感兴趣。皮质抑制的一个显著特性是它如何紧密地平衡兴奋。抑制电流不仅在平均水平上与兴奋性电流匹配，而且在毫秒时间尺度上跟踪它们，无论它们是由外部刺激还是自发波动引起的。我们结合实验证据，回顾了最近的理论方法，这些方法研究了这种紧密平衡对编码和计算的优势。这些研究表明，可能需要对占主导地位的观点进行修正，即神经元通过泊松噪声干扰的 firing rate 来表示信息。相反，紧密的兴奋/抑制平衡可能是一种高度协作编码的特征，比泊松率编码精确几个数量级。此外，紧密的平衡可能为皮质神经元构建高维群体编码和学习输入的复杂函数提供模板。
