Feedback-dependent generalization
Feedback-dependent generalization
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DOI：
10.1152/jn.00247.2012
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发表时间：
2013-01-01
影响因子：
2.5
通讯作者：
Ivry, Richard B.
中科院分区：
文献类型：
--
作者：
Taylor, Jordan A.;Hieber, Laura L.;Ivry, Richard B.
Taylor JA，Hieber LL，Ivry RB.反馈依赖泛化。J Neurophysiol 109：202-215，2013.首次发表于2012年10月10日; doi：10.1152/jn.00247.2012.-泛化提供了一个窗口，在运动学习过程中发生的表征变化。神经网络模型在揭示神经表示如何限制泛化程度方面是不可或缺的。具体而言，两个关键特征被认为是定义泛化模式。首先，泛化受到底层神经元属性的约束;对于定向调谐单元，泛化的程度受到调谐函数宽度的限制。第二，误差信号用于更新感觉运动图，以使期望输出和实际输出保持一致，梯度下降学习规则确保误差在导致误差的那些单元中产生变化。在以往的研究中，任务特异性效应的泛化已被归因于不同的神经调谐功能。在这里，我们要问的是，泛化功能的差异是否可能来自特定任务的错误信号。我们系统地改变视觉错误信息的视觉适应任务，发现这种操作导致定性差异的概括。一个神经网络模型表明，这些差异的结果，误差反馈处理操作的一个均匀的和不变的一组调谐功能。与从模型中得出的新预测一致，增加训练方向的数量会导致泛化函数的特定扭曲。两者合计，行为和建模结果提供了一个简约的帐户的泛化，是基于利用反馈信息更新的感觉运动地图与稳定的调谐功能。
Taylor JA, Hieber LL, Ivry RB. Feedback-dependent generalization. J Neurophysiol 109: 202-215, 2013. First published October 10, 2012; doi:10.1152/jn.00247.2012.-Generalization provides a window into the representational changes that occur during motor learning. Neural network models have been integral in revealing how the neural representation constrains the extent of generalization. Specifically, two key features are thought to define the pattern of generalization. First, generalization is constrained by the properties of the underlying neural units; with directionally tuned units, the extent of generalization is limited by the width of the tuning functions. Second, error signals are used to update a sensorimotor map to align the desired and actual output, with a gradient-descent learning rule ensuring that the error produces changes in those units responsible for the error. In prior studies, task-specific effects in generalization have been attributed to differences in neural tuning functions. Here we ask whether differences in generalization functions may arise from task-specific error signals. We systematically varied visual error information in a visuomotor adaptation task and found that this manipulation led to qualitative differences in generalization. A neural network model suggests that these differences are the result of error feedback processing operating on a homogeneous and invariant set of tuning functions. Consistent with novel predictions derived from the model, increasing the number of training directions led to specific distortions of the generalization function. Taken together, the behavioral and modeling results offer a parsimonious account of generalization that is based on the utilization of feedback information to update a sensorimotor map with stable tuning functions.