Trial-to-trial dynamics and learning in a generalized, redundant reaching task
Trial-to-trial dynamics and learning in a generalized, redundant reaching task
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DOI：
10.1152/jn.00951.2011
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发表时间：
2013-01-01
影响因子：
2.5
通讯作者：
Cusumano, Joseph P.
中科院分区：
文献类型：
--
作者：
Dingwell, Jonathan B.;Smallwood, Rachel F.;Cusumano, Joseph P.
Dingwell JB，Smallwood RF，Cusumano JP.广义冗余到达任务中的试验到试验动力学和学习。J Neurophysiol 109：225-237，2013.首次发表于2012年10月10日; doi：10.1152/jn.00951.2011.-如果人类利用任务冗余作为一种通用策略，那么即使冗余与任务本身的物理实现无关，他们也应该这样做。在这里，我们导出了一系列目标函数，明确定义了单向到达的距离（D）和时间（T）之间的无限可能冗余。满足任何特定目标函数的所有[T，D]组合定义了一个目标等价流形（GEM）。我们测试了人类如何学习两个这样的功能，D/T = c（恒定速度）和D.T = c，这两个功能非常不同，但都可以通过神经生理学和生物力学上相似的伸展运动来实现。受试者从来没有明确显示任何关系，但只是指示尽量减少他们的错误。受试者表现出显着的学习和巩固的学习任务。初始错误幅度较高，但学习速度更快，D.T任务比D/T任务。首先学习D/T任务有助于随后学习D.T任务。相反，先学习D.T任务会干扰随后的D/T任务学习。试验间动态分析表明，受试者主动纠正垂直于每个GEM的偏差比沿着每个GEM的偏差更快，两项任务的程度相同，尽管D/T任务的方差比显着更大。单独的方差测量未能捕获试验间对照的关键特征。人类积极利用这些抽象的任务冗余，即使他们没有必要。他们没有使用现成的替代战略，可以实现同样的性能。
Dingwell JB, Smallwood RF, Cusumano JP. Trial-to-trial dynamics and learning in a generalized, redundant reaching task. J Neurophysiol 109: 225-237, 2013. First published October 10, 2012; doi:10.1152/jn.00951.2011.-If humans exploit task redundancies as a general strategy, they should do so even if the redundancy is decoupled from the physical implementation of the task itself. Here, we derived a family of goal functions that explicitly defined infinite possible redundancies between distance (D) and time (T) for unidirectional reaching. All [T, D] combinations satisfying any specific goal function defined a goal-equivalent manifold (GEM). We tested how humans learned two such functions, D/T = c (constant speed) and D.T = c, that were very different but could both be achieved by neurophysiologically and biomechanically similar reaching movements. Subjects were never explicitly shown either relationship, but only instructed to minimize their errors. Subjects exhibited significant learning and consolidation of learning for both tasks. Initial error magnitudes were higher, but learning rates were faster, for the D.T task than for the D/T task. Learning the D/T task first facilitated subsequent learning of the D.T task. Conversely, learning the D.T task first interfered with subsequent learning of the D/T task. Analyses of trial-to-trial dynamics demonstrated that subjects actively corrected deviations perpendicular to each GEM faster than deviations along each GEM to the same degree for both tasks, despite exhibiting significantly greater variance ratios for the D/T task. Variance measures alone failed to capture critical features of trial-to-trial control. Humans actively exploited these abstract task redundancies, even though they did not have to. They did not use readily available alternative strategies that could have achieved the same performance.