Department of Basic Neurosciences, School of Medicine, University of Geneva, Geneva, Switzerland.
PLoS One. 2012;7(1):e30155. doi: 10.1371/journal.pone.0030155. Epub 2012 Jan 17.
How do neural networks encode sensory information? Following sensory stimulation, neural coding is commonly assumed to be based on neurons changing their firing rate. In contrast, both theoretical works and experiments in several sensory systems showed that neurons could encode information as coordinated cell assemblies by adjusting their spike timing and without changing their firing rate. Nevertheless, in the olfactory system, there is little experimental evidence supporting such model.
METHODOLOGY/PRINCIPAL FINDINGS: To study these issues, we implanted tetrodes in the olfactory bulb of awake mice to record the odorant-evoked activity of mitral/tufted (M/T) cells. We showed that following odorant presentation, most M/T neurons do not significantly change their firing rate over a breathing cycle but rather respond to odorant stimulation by redistributing their firing activity within respiratory cycles. In addition, we showed that sensory information can be encoded by cell assemblies composed of such neurons, thus supporting the idea that coordinated populations of globally rate-invariant neurons could be efficiently used to convey information about the odorant identity. We showed that different coding schemes can convey high amount of odorant information for specific read-out time window. Finally we showed that the optimal readout time window corresponds to the duration of gamma oscillations cycles.
We propose that odorant can be encoded by population of cells that exhibit fine temporal tuning of spiking activity while displaying weak or no firing rate change. These cell assemblies may transfer sensory information in spiking packets sequence using the gamma oscillations as a clock. This would allow the system to reach a tradeoff between rapid and accurate odorant discrimination.
神经网络如何编码感官信息？在感官刺激后，通常假设神经编码是基于神经元改变其放电率。相比之下，在几个感官系统中，理论工作和实验都表明，神经元可以通过调整其尖峰时间而不改变其放电率，从而将信息编码为协调的细胞集合。然而，在嗅觉系统中，几乎没有实验证据支持这种模型。
方法/主要发现：为了研究这些问题，我们在清醒小鼠的嗅球中植入四极管，以记录气味诱发的僧帽细胞/丛细胞（M/T）的活动。我们表明，在气味呈现后，大多数 M/T 神经元在呼吸周期内不会显著改变其放电率，而是通过在呼吸周期内重新分配其放电活动来响应气味刺激。此外，我们表明，信息可以通过由这些神经元组成的细胞集合进行编码，从而支持这样的观点，即协调的全局不变率神经元群体可以有效地用于传递关于气味身份的信息。我们表明，不同的编码方案可以为特定的读取时间窗口编码高信息量的气味信息。最后，我们表明最佳的读取时间窗口对应于伽马振荡周期的持续时间。
我们提出，气味可以通过表现出精细时间调谐的放电活动的细胞群体进行编码，同时显示出微弱或没有放电率变化。这些细胞集合可以通过伽马振荡作为时钟，以尖峰脉冲包序列的形式传递感官信息。这将允许系统在快速和准确的气味识别之间达到权衡。
