Barreiro Andrea K, Gautam Shree Hari, Shew Woodrow L, Ly Cheng
Department of Mathematics, Southern Methodist University, Dallas, Texas, United States of America.
Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.
PLoS Comput Biol. 2017 Oct 2;13(10):e1005780. doi: 10.1371/journal.pcbi.1005780. eCollection 2017 Oct.
Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data. We apply our new technique to dual micro-electrode array in vivo recordings from two distinct regions: olfactory bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i) inhibition within the afferent region (OB) has to be weaker than the inhibition within PC, ii) excitation from PC to OB is generally stronger than excitation from OB to PC, iii) excitation from PC to OB and inhibition within PC have to both be relatively strong compared to presynaptic inputs from OB. These predictions are validated in a spiking neural network model of the OB-PC pathway that satisfies the many constraints from our experimental data. We find when the derived relationships are violated, the spiking statistics no longer satisfy the constraints from the data. In principle this modeling framework can be adapted to other systems and be used to investigate relationships between other neural attributes besides network connection strengths. Thus, this work can serve as a guide to further investigations into the relationships of various neural attributes within and across different regions during sensory processing.
确定在感觉处理过程中区域内和区域间的突触耦合是如何被调制的，是神经科学中的一个重要课题。电生理记录提供了关于神经放电的详细信息，但传统上局限于皮层的特定区域或层。在这里，我们基于从两个区域同时记录的放电活动的实验测量，开发了新的理论方法来研究两个脑区之间以及内部的相互作用。通过系统地将实验获得的放电统计数据与（高效计算的）模型放电率统计数据进行比较，我们在模型参数空间中确定了与实验数据一致的区域。我们将新技术应用于来自两个不同区域——嗅球（OB）和前梨状皮层（PC）的双微电极阵列体内记录。我们的分析预测：i）传入区域（OB）内的抑制必须比PC内的抑制弱，ii）从PC到OB的兴奋通常比从OB到PC的兴奋强，iii）与来自OB的突触前输入相比，从PC到OB的兴奋和PC内的抑制都必须相对较强。这些预测在满足我们实验数据诸多约束的OB - PC通路的脉冲神经网络模型中得到了验证。我们发现，当违反推导的关系时，放电统计数据不再满足数据的约束。原则上，这个建模框架可以适用于其他系统，并用于研究除网络连接强度之外的其他神经属性之间的关系。因此，这项工作可以作为进一步研究感觉处理过程中不同区域内和跨区域的各种神经属性之间关系的指南。
