Department of Psychology, Colorado State University, Fort Collins, CO 80523, USA.
Neuroimage. 2010 Apr 1;50(2):644-56. doi: 10.1016/j.neuroimage.2009.11.083. Epub 2009 Dec 5.
We dissociated the contributions to learning of four corticostriatal "loops" (interacting striatal and cortical regions): motor (putamen and motor cortex), visual (posterior caudate and visual cortex), executive (anterior caudate and prefrontal cortex), and motivational (ventral striatum and ventromedial frontal cortex). Subjects learned to categorize individual repeated images into one of two arbitrary categories via trial and error. We identified (1) regions sensitive to correct categorization, categorization learning, and feedback valence; (2) regions sensitive to prediction error (violation of feedback expectancy) and reward prediction (expected feedback associated with category response) using reinforcement learning modeling; and (3) directed influences between regions using Granger causality modeling. Each loop showed a unique pattern of sensitivity to each of these factors. Both the motor and visual loops were involved in acquisition of categorization ability: activity during correct categorization increased across learning and was sensitive to reward prediction. However, the posterior caudate received directed influence from visual cortex, whereas the putamen exerted directed influence on motor cortex. The motivational and executive loops were involved in feedback processing: both regions were sensitive to feedback valence, which interacted with learning across scans. However, the motivational loop activity reflected prediction error, whereas executive loop activity reflected reward prediction, consistent with the executive loop role in integrating reward and action. Granger causality modeling found directed influences between striatal and cortical regions within each loop. Across loops, the motor loop exerted directed influence on the executive loop which is consistent with the role of the executive loop in integrating feedback with stimulus-response history.
我们分离了四个皮质纹状体“回路”（相互作用的纹状体和皮质区域）对学习的贡献：运动（壳核和运动皮质）、视觉（后尾状核和视觉皮质）、执行（前尾状核和前额叶皮质）和动机（腹侧纹状体和腹内侧前额叶皮质）。受试者通过反复试验学会将单个重复图像分类到两个任意类别之一。我们确定了（1）对正确分类、分类学习和反馈效价敏感的区域；（2）使用强化学习建模对预测误差（违反反馈预期）和奖励预测（与类别反应相关的预期反馈）敏感的区域；（3）使用格兰杰因果关系建模确定区域之间的定向影响。每个回路都表现出对这些因素的独特敏感性模式。运动和视觉回路都参与了分类能力的获得：正确分类时的活动随着学习的进行而增加，并且对奖励预测敏感。然而，后尾状核接收到来自视觉皮层的定向影响，而壳核则对运动皮层施加了定向影响。动机和执行回路参与了反馈处理：两个区域都对反馈效价敏感，反馈效价在扫描过程中与学习相互作用。然而，动机回路的活动反映了预测误差，而执行回路的活动反映了奖励预测，这与执行回路在整合奖励和动作方面的作用一致。格兰杰因果关系建模发现每个回路中纹状体和皮质区域之间存在定向影响。在回路之间，运动回路对执行回路施加了定向影响，这与执行回路在将反馈与刺激-反应历史整合在一起的作用一致。
