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Delayed mutual information infers patterns of synaptic connectivity in a proprioceptive neural network

机译:延迟的互信息推断本体感受神经网络中突触连接的模式

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Understanding the patterns of interconnections between neurons in complex networks is an enormous challenge using traditional physiological approaches. Here we combine the use of an information theoretic approach with intracellular recording to establish patterns of connections between layers of interneurons in a neural network responsible for mediating reflex movements of the hind limb of an insect. By analysing delayed mutual information of the synaptic and spiking responses of sensory neurons, spiking and nonspiking interneurons in response to movement of a joint receptor that monitors the position of the tibia relative to the femur, we are able to predict the patterns of interconnections between the layers of sensory neurons and interneurons in the network, with results matching closely those known from the literature. In addition, we use cross-correlation methods to establish the sign of those interconnections and show that they also show a high degree of similarity with those established for these networks over the last 30 years. The method proposed in this paper has great potential to elucidate functional connectivity at the neuronal level in many different neuronal networks.
机译:使用传统的生理学方法,了解复杂网络中神经元之间的互连模式是一项巨大的挑战。在这里,我们结合使用信息理论方法和细胞内记录来建立负责介导昆虫后肢反射运动的神经网络中神经元层之间的连接模式。通过分析感觉神经元的突触和尖峰反应的延迟相互信息,尖峰和非尖峰的中间神经元对监测胫骨相对于股骨位置的关节受体运动的响应,我们能够预测两者之间的互连模式网络中的感觉神经元和中间神经元层,其结果与文献中已知的结果非常接近。此外,我们使用互相关方法来建立这些互连的符号,并表明它们在过去30年中也与为这些网络建立的互连具有高度相似性。本文提出的方法在阐明许多不同神经元网络中神经元级别的功能连通性方面具有巨大潜力。

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