A Computational Model for a Multi-Goal Spatial Navigation Task inspired by Rodent Studies
A Computational Model for a Multi-Goal Spatial Navigation Task inspired by Rodent Studies
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DOI：
10.1109/ijcnn.2019.8851852
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发表时间：
2019-07
期刊：
影响因子：
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通讯作者：
Martín Llofriu;Pablo Scleidorovich;G. Tejera;M. Contreras;Tatiana Pelc;J. Fellous;A. Weitzenfeld
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文献类型：
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作者：
Martín Llofriu;Pablo Scleidorovich;G. Tejera;M. Contreras;Tatiana Pelc;J. Fellous;A. Weitzenfeld
我们提出了一个生物启发的计算模型的基础上，最近的研究表明，其纵轴参与复杂的空间导航的海马啮齿动物海马。虽然海马的两极，即隔（背侧）和颞（腹侧），编码空间信息;隔区传统上被认为更多地是导航和动作选择;而颞极更多地涉及学习和动机。在这项工作中，我们假设海马轴的间隔-时间组织也提供了一个多尺度的空间表示，可以利用复杂的啮齿动物导航。为了验证这一假设，我们开发了一个多尺度模型的海马评估它与模拟大鼠的多目标任务，最初在一个简化的环境中，然后在一个更复杂的环境中，引入多个障碍。除了海马体提供的环境的空间表示，该模型包括一个演员批评家的框架，为不同的任务的动机学习。
We present a biologically-inspired computational model of the rodent hippocampus based on recent studies of the hippocampus showing that its longitudinal axis is involved in complex spatial navigation. While both poles of the hippocampus, i.e. septal (dorsal) and temporal (ventral), encode spatial information; the septal area has traditionally been attributed more to navigation and action selection; whereas the temporal pole has been more involved with learning and motivation. In this work we hypothesize that the septal-temporal organization of the hippocampus axis also provides a multi-scale spatial representation that may be exploited during complex rodent navigation. To test this hypothesis, we developed a multi-scale model of the hippocampus evaluated it with a simulated rat on a multi-goal task, initially in a simplified environment, and then on a more complex environment where multiple obstacles are introduced. In addition to the hippocampus providing a spatial representation of the environment, the model includes an actor-critic framework for the motivated learning of the different tasks.