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A simulator for the analysis of neuronal ensemble activity: application to reaching tasks

机译:用于分析神经元集合活动的模拟器:达到任务的应用

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A biologically based, multi-cortical computational model was developed to investigate how ensembles of neurons learn to execute a three-dimensional reaching task. The model produces outputs of spike trains that can be analyzed using a variety of multivariate analysis tools. Simulations show that after learning, the model neurons exhibit broad directional tuning that depend on the defined muscle directions of the simulated arm, and that these neurons form functional clusters within cortical areas. The utility of the model is demonstrated by testing arm movement prediction strategies using ensemble activity.
机译:开发了一种生物学基础的多皮质计算模型,以研究神经元的乐曲学会如何执行三维到达任务。该模型产生尖峰列车的输出,可以使用各种多变量分析工具分析。仿真表明,在学习之后,模型神经元表现出宽方向调谐,这取决于模拟臂的限定肌肉方向,并且这些神经元在皮质区域内形成功能簇。通过使用集合活动测试臂移动预测策略来证明模型的实用性。

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