Action selection in multi-effector decision making.
Action selection in multi-effector decision making.
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DOI：
10.1016/j.neuroimage.2012.12.001
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发表时间：
2013-04-15
期刊：
影响因子：
5.7
通讯作者：
Daw ND
中科院分区：
文献类型：
--
作者：
Madlon-Kay S;Pesaran B;Daw ND
对运动的决策和强化学习受到维度灾难的影响：可能的运动空间太大，无法搜索，甚至无法完整地表示。当动作只涉及单个效应器时，这个问题可以通过单独考虑该效应器来改善;因此，大脑的感觉运动系统可以通过为每个效应器单独表示值和动作来细分选择。然而，对于许多动作，诸如弹钢琴，效应器的动作的值（例如，手）不可分割地依赖于其他效应器的动作。根据定义，这种协调的多效应器动作的值不能由效应器特异性动作值表示，例如在顶叶和运动前区中最广泛研究的那些。对于这样的行为，一个可能的解决方案是根据对不同商品或选项的更抽象的评估进行选择，然后将其映射到必要的运动动作上。这种方法将学习和决策问题与多效应器运动规划问题分开，学习和决策问题通常比可能的运动空间维度更低。腹内侧前额叶皮层（vmPFC）被认为包含基于商品的价值信号，因此我们假设该区域可能优先驱动多效应器动作选择。为了研究大脑是如何解决这个问题的，我们使用功能性磁共振成像技术比较了人类在奖励学习任务中BOLD活动的模式，在这些任务中，选择是通过单手或双手动作进行的，而在后一种情况下，反应要求与双手的评估密不可分。我们在双侧内侧运动皮层和vmPFC中发现了价值信号，与以前的研究一致，内侧运动价值信号包含指示效应器特异性的对侧偏差，而vmPFC价值信号没有表现出可检测的效应器特异性。虽然两个区域的价值信号在双手和单手条件下显着不同，vmPFC值区域表现出增强的连接与内侧运动皮层在双手比在单手的选择。这一特定区域，即前中扣带皮层，被认为是将主观价值信号与运动控制中心联系起来的枢纽。这些结果是一致的想法，而评价单方面的行动可能subserved由效应器特定的网络，复杂的多效应器的行动优先牵连运动区域和前额叶区域之间的通信，这可能反映了增加自上而下的输入到运动区域，以指导行动选择。
Decision making and reinforcement learning over movements suffer from the curse of dimensionality: the space of possible movements is too vast to search or even represent in its entirety. When actions involve only a single effector, this problem can be ameliorated by considering that effector separately; accordingly, the brain’s sensorimotor systems can subdivide choice by representing values and actions separately for each effector. However, for many actions, such as playing the piano, the value of an action by an effector (e.g., a hand) depends inseparably on the actions of other effectors. By definition, the values of such coordinated multi-effector actions cannot be represented by effector-specific action values, such as those that have been most extensively investigated in parietal and premotor regions. For such actions, one possible solution is to choose according to more abstract valuations over different goods or options, which can then be mapped onto the necessary motor actions. Such an approach separates the learning and decision problem, which will often be lower-dimensional than the space of possible movements, from the multi-effector movement planning problem. The ventromedial prefrontal cortex (vmPFC) is thought to contain goods-based value signals, so we hypothesized that this region might preferentially drive multi-effector action selection. To examine how the brain solves this problem, we used fMRI to compare patterns of BOLD activity in humans during reward learning tasks in which options were selected through either unimanual or bimanual actions, and in which the response requirements in the latter condition inseparably coupled valuation across both hands. We found value signals in the bilateral medial motor cortex and vmPFC, and consistent with previous studies, the medial motor value signals contained contra-lateral biases indicating effector-specificity, while the vmPFC value signals did not exhibit detectable effector specificity. Although neither region’s value signaling differed significantly between bimanual and unimanual conditions, the vmPFC value region showed enhanced connectivity with the medial motor cortex during bimanual than during unimanual choices. The specific region implicated, the anterior mid-cingulate cortex, is thought to act as a hub that links subjective value signals to motor control centers. These results are consistent with the idea that while valuation for unilateral actions may be subserved by an effector-specific network, complex multi-effector actions preferentially implicate communication between motor regions and prefrontal regions, which may reflect increased top-down input into motor regions to guide action selection.
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