Computational modelling reveals distinct patterns of cognitive and physical motivation in elite athletes.
Computational modelling reveals distinct patterns of cognitive and physical motivation in elite athletes.
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DOI：
10.1038/s41598-018-30220-3
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发表时间：
2018-08-08
影响因子：
4.6
通讯作者：
Husain M
中科院分区：
文献类型：
--
作者：
Chong TT;Apps MAJ;Giehl K;Hall S;Clifton CH;Husain M
努力可以在认知和身体上被感知，但在每个领域投入努力的动机背后的计算机制仍然不清楚。特别是，它是未知的，无论是密集的体育锻炼与特定于该领域的更高的动机，或者它是否伴随着相应的认知动机的变化。在这里，我们测试了一组牛津大学的优秀赛艇运动员，并将他们的行为与匹配的非运动控制进行了比较。我们对参与者进行了两项涉及认知或身体努力的任务的培训。然后，他们决定在基线低水平的努力获得低回报，还是更高水平的努力获得更高回报。认知任务和体力任务分别进行选择，这使我们能够在每个领域独立地对动机进行计算建模。正如预期的那样，运动员愿意比非运动员付出更大的体力。然而，关键的是，基于认知努力的决策的性质在不同的群体之间是不同的，运动员的努力折扣模式是凹的，而非运动员的努力折扣模式是凸的。这些数据表明，运动员更大的身体驱动力伴随着根本不同的认知努力折扣模式，并表明这两个领域的动机之间存在复杂的关系。
Effort can be perceived both cognitively and physically, but the computational mechanisms underlying the motivation to invest effort in each domain remain unclear. In particular, it is unknown whether intensive physical training is associated with higher motivation specific to that domain, or whether it is accompanied by corresponding changes in cognitive motivation. Here, we tested a group of elite Oxford University rowers, and compared their behaviour to matched non-athletic controls. We trained participants on two tasks involving cognitive or physical effort. They then decided between a baseline low level of effort for low reward, versus higher levels of effort for higher rewards. Separate choices were made for the cognitive and physical tasks, which allowed us to computationally model motivation in each domain independently. As expected, athletes were willing to exert greater amounts of physical effort than non-athletes. Critically, however, the nature of cognitive effort-based decisions was different between groups, with a concave pattern of effort discounting for athletes but a convex pattern for non-athletes. These data suggest that the greater physical drive in athletes is accompanied by fundamentally different patterns of cognitive effort discounting, and suggests a complex relationship between motivation in the two domains.
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影响因子：
9.8
作者：
Chong TT;Apps M;Giehl K;Sillence A;Grima LL;Husain M
通讯作者：
Husain M
影响因子：
4.6
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