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Distributed processing of sensory information in the leech. III. A dynamical neural network model of the local bending reflex

机译:水le中的感官信息的分布式处理。三局部弯曲反射的动力学神经网络模型

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摘要

The subpopulation of identified interneurons in the local bending reflex receive multiple inputs from dorsal and ventral mechanoreceptors and have outputs to dorsal and ventral motor neurons. Their connections suggest a distributed processing mechanism in which withdrawal from dorsal, ventral, or lateral stimuli is controlled by a single population of approximately 40 multifunctional interneurons, but it is unclear whether additional interneurons dedicated to particular inputs are needed to account for each kind of bend. We therefore asked whether a model could be constructed that reproduced all behaviors without dedicated interneurons. Interneurons in the model were constrained to receive both dorsal and ventral inputs. Connection strengths were adjusted by gradient descent optimization until the model reproduced the amplitude and time course of motor neuron synaptic potentials in intracellular recordings of the response to many different stimuli. After optimization, the similarity between model and identified interneurons showed that additional dedicated interneurons are not necessary to produce all forms of the behavior. Successful optimization of networks with many fewer interneurons showed that the 40-interneuron network is redundant, raising the possibility that the interneurons have additional functions. Finally, optimizing networks with additional constraints produced better matches to some of the identified interneurons and showed that local bending can be produced by two populations of interneurons: one with outputs consistent with dorsal bending, the other with ventral bending. This suggests a simple model in which two principal types of interneurons produce many different behaviors and predicts the type of interneuron that remains to be identified.
机译:局部弯曲反射中所识别的中间神经元的亚群从背侧和腹侧机械感受器接收多个输入,并向背侧和腹侧运动神经元输出。他们的联系暗示了一种分布式处理机制,其中从背,腹或侧向刺激的撤退由大约40个多功能中间神经元的单个种群控制,但是尚不清楚是否需要专用于特定输入的额外中间神经元来解决每种类型的弯曲。因此,我们询问是否可以构建一个无需专用中间神经元就能复制所有行为的模型。模型中的中间神经元被约束为同时接收背侧和腹侧输入。通过梯度下降优化来调节连接强度,直到该模型在对许多不同刺激的反应的细胞内记录中再现了运动神经元突触电位的幅度和时间过程。经过优化后,模型和已识别的中间神经元之间的相似性表明,不需要额外的专用中间神经元即可产生所有形式的行为。用更少的中间神经元成功地优化网络表明40中间神经元网络是多余的,从而增加了中间神经元具有附加功能的可能性。最后,优化具有附加约束的网络可以更好地匹配某些已识别的中间神经元,并表明局部弯曲可以由两个中间神经元群产生:一个中间神经元的输出与背侧弯曲一致,另一个与腹侧弯曲。这提出了一个简单的模型,其中两种主要类型的中间神经元产生许多不同的行为,并预测有待确定的中间神经元的类型。

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