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The neuronal substrate underlying order and interval representations in sequential tasks: A biologically based robot study

机译:顺序任务中神经元底物的顺序和区间表示:基于生物学的机器人研究

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Sequence learning tasks depend on the ability to acquire and control the order of actions and their proper timing. Several studies have shown that in sequence learning different areas of the brain are involved when recalling the order of actions and their proper interval. One hypothesis proposes that two separate areas of the brain interact with each other, one computes order while the other would compute the interval. A second hypothesis proposes that one area computes both, order and interval. To better understand how this computation of order and interval might be realized by the brain, we developed a robot based architecture and investigated the behavioral and architectural implications of these two hypothesis: one or two neuronal areas computing order and interval. Using a sequence learning foraging task we show that performance is enhanced in case of distributed processes. However, we show that as a drawback, explicit interval information can not be reconstructed.
机译:顺序学习任务取决于获取和控制动作顺序及其正确时机的能力。多项研究表明,在回忆动作顺序及其适当的间隔时,需要依次学习大脑的不同区域。一种假设提出大脑的两个独立区域相互交互,一个区域计算顺序,而另一个区域计算间隔。第二个假设提出一个区域同时计算顺序和间隔。为了更好地理解大脑如何实现顺序和间隔的计算,我们开发了一种基于机器人的体系结构,并研究了这两个假设的行为和体系结构含义:一个或两个神经元区域计算顺序和间隔。使用序列学习搜寻任务,我们表明在分布式过程的情况下性能得到了提高。但是,我们表明,作为一个缺点,无法重构显式间隔信息。

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