Stimulus and Network Dynamics Collide in a Ratiometric Model of the Antennal Lobe Macroglomerular Complex
Stimulus and Network Dynamics Collide in a Ratiometric Model of the Antennal Lobe Macroglomerular Complex
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DOI：
10.1371/journal.pone.0029602
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发表时间：
2012-01-10
期刊：
影响因子：
3.7
通讯作者：
Pearce, Timothy Charles
中科院分区：
文献类型：
--
作者：
Chong, Kwok Ying;Capurro, Alberto;Pearce, Timothy Charles
时间被认为是嗅觉中一个重要的编码维度，因为神经群体对恒定刺激产生特定于气味的时空响应。然而，在信息素介导的趋风搜索昆虫必须区分混合组分的快速时变输入的特定比例。因此，嗅觉处理和自然刺激的内在动力学可能会发生冲突，从而混淆比率信息。在本文中，我们使用的昆虫触角叶的巨球复合物的计算模型，研究网络和刺激动力学之间的这种潜在的碰撞的比率信息的影响。我们发现，该模型表现出两种不同的动力学制度，这取决于抑制性中间神经元之间的连接模式（我们称为固定点吸引子和极限环吸引子），这两个产生特定比例的轨迹在投影神经元输出人口，让人想起的时间模式和周期性超极化观察嗅触角叶神经元。我们比较了两个相应的人口代码报告比率混合信息的昆虫大脑的更高的中心的性能。我们的关键发现是，虽然动态丰富的极限环吸引时空代码是更快，更有效地在一定条件下传输混合信息，它也更容易网络和刺激动力学之间的干扰，从而降低自然输入条件下的比率信息。我们的研究结果表明，丰富的内在生成的网络动态可以提供一个强大的手段，编码多维刺激具有高精度和高效率，但只有当孤立的刺激动态。刺激的时间动态和神经活动的时间模式之间的这种干扰构成了神经系统在面对自然输入时必须成功解决的真实的挑战。
Time is considered to be an important encoding dimension in olfaction, as neural populations generate odour-specific spatiotemporal responses to constant stimuli. However, during pheromone mediated anemotactic search insects must discriminate specific ratios of blend components from rapidly time varying input. The dynamics intrinsic to olfactory processing and those of naturalistic stimuli can therefore potentially collide, thereby confounding ratiometric information. In this paper we use a computational model of the macroglomerular complex of the insect antennal lobe to study the impact on ratiometric information of this potential collision between network and stimulus dynamics. We show that the model exhibits two different dynamical regimes depending upon the connectivity pattern between inhibitory interneurons (that we refer to as fixed point attractor and limit cycle attractor), which both generate ratio-specific trajectories in the projection neuron output population that are reminiscent of temporal patterning and periodic hyperpolarisation observed in olfactory antennal lobe neurons. We compare the performance of the two corresponding population codes for reporting ratiometric blend information to higher centres of the insect brain. Our key finding is that whilst the dynamically rich limit cycle attractor spatiotemporal code is faster and more efficient in transmitting blend information under certain conditions it is also more prone to interference between network and stimulus dynamics, thus degrading ratiometric information under naturalistic input conditions. Our results suggest that rich intrinsically generated network dynamics can provide a powerful means of encoding multidimensional stimuli with high accuracy and efficiency, but only when isolated from stimulus dynamics. This interference between temporal dynamics of the stimulus and temporal patterns of neural activity constitutes a real challenge that must be successfully solved by the nervous system when faced with naturalistic input.