Neuroscience Program, University of Illinois at Urbana-Champaign , Urbana, Illinois.
Beckman Institute for Advanced Science and Technology , Urbana, Illinois.
J Neurophysiol. 2018 Dec 1;120(6):2730-2744. doi: 10.1152/jn.00012.2018. Epub 2018 Sep 5.
The impact of thalamic state on information transmission to the cortex remains poorly understood. This limitation exists due to the rich dynamics displayed by thalamocortical networks and because of inadequate tools to characterize those dynamics. Here, we introduce a novel estimator of mutual information and use it to determine the impact of a computational model of thalamic state on information transmission. Using several criteria, this novel estimator, which uses an adaptive partition, is shown to be superior to other mutual information estimators with uniform partitions when used to analyze simulated spike train data with different mean spike rates, as well as electrophysiological data from simultaneously recorded neurons. When applied to a thalamocortical model, the estimator revealed that thalamocortical cell T-type calcium current conductance influences mutual information between the input and output from this network. In particular, a T-type calcium current conductance of ~40 nS appears to produce maximal mutual information between the input to this network (conceptualized as afferent input to the thalamocortical cell) and the output of the network at the level of a layer 4 cortical neuron. Furthermore, at particular combinations of inputs to thalamocortical and thalamic reticular nucleus cells, thalamic cell bursting correlated strongly with recovery of mutual information between thalamic afferents and layer 4 neurons. These studies suggest that the novel mutual information estimator has advantages over previous estimators and that thalamic reticular nucleus activity can enhance mutual information between thalamic afferents and thalamorecipient cells in the cortex. NEW & NOTEWORTHY In this study, a novel mutual information estimator was developed to analyze information flow in a model thalamocortical network. Our findings suggest that this estimator is a suitable tool for signal transmission analysis, particularly in neural circuits with disparate firing rates, and that the thalamic reticular nucleus can potentiate ascending sensory signals, while thalamic recipient cells in the cortex can recover mutual information in ascending sensory signals that is lost due to thalamic bursting.
丘脑状态对向皮层传递信息的影响仍知之甚少。这种局限性的存在是由于丘脑皮质网络表现出丰富的动力学特性，以及缺乏表征这些动力学特性的适当工具。在这里，我们引入了一种新的互信息估计器，并使用它来确定丘脑状态的计算模型对信息传递的影响。使用多个标准，这种新的估计器（使用自适应分区）在分析具有不同平均尖峰率的模拟尖峰训练数据以及同时记录的神经元的电生理数据时，优于具有均匀分区的其他互信息估计器。当应用于丘脑皮质模型时，该估计器表明，丘脑皮质细胞 T 型钙电流电导会影响该网络的输入和输出之间的互信息。特别是，约 40nS 的 T 型钙电流电导似乎会在该网络的输入（概念化为丘脑皮质细胞的传入输入）和皮质 4 层神经元的网络输出之间产生最大的互信息。此外，在特定的丘脑皮质和丘脑网状核细胞输入组合下，丘脑细胞爆发与丘脑传入和皮质 4 层神经元之间互信息的恢复密切相关。这些研究表明，新的互信息估计器具有优于以前的估计器的优势，并且丘脑网状核活动可以增强皮质中丘脑传入和丘脑接受细胞之间的互信息。在这项研究中，开发了一种新的互信息估计器来分析模型丘脑皮质网络中的信息流。我们的发现表明，该估计器是一种适合信号传输分析的工具，特别是在具有不同放电率的神经电路中，并且丘脑网状核可以增强上行感觉信号，而皮质中的丘脑接受细胞可以恢复由于丘脑爆发而丢失的上行感觉信号中的互信息。
