Sensory integration for reaching: models of optimality in the context of behavior and the underlying neural circuits.
Sensory integration for reaching: models of optimality in the context of behavior and the underlying neural circuits.
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DOI：
10.1016/b978-0-444-53752-2.00004-7
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发表时间：
2011
影响因子：
--
通讯作者：
Sabes, Philip N.
中科院分区：
文献类型：
--
作者：
Sabes, Philip N.
关键词：
尽管多感觉整合已经在行为层面得到了很好的建模，但这些行为模型和底层神经回路之间的联系仍然不清楚。对于运动计划和执行过程中的感觉统合问题，这种差距甚至更大。困难在于将简单的感觉统合模型应用于运动控制所需的复杂计算以及执行这些计算的大型大脑区域网络。在这里，我回顾了运动计划过程中多感官整合的心理物理学、计算和生理学工作，重点是目标导向的达成。我认为感官转变必须在任何建模工作中发挥核心作用。特别是这些转换的统计特性很大程度上影响了下游信号的组合方式。因此，我们的最佳整合模型预计仅适用于“局部”，即独立于每个大脑区域。我建议，如果人们不将顶叶感觉运动区域的集合视为一组特定于任务的域，而是将其视为灵活组合以驱动下游活动和行为的复杂感觉运动表征的调色板，则局部最优性可以与全局最优行为相协调。
Although multisensory integration has been well modeled at the behavioral level, the link between these behavioral models and the underlying neural circuits is still not clear. This gap is even greater for the problem of sensory integration during movement planning and execution. The difficulty lies in applying simple models of sensory integration to the complex computations that are required for movement control and to the large networks of brain areas that perform these computations. Here I review psychophysical, computational, and physiological work on multisensory integration during movement planning, with an emphasis on goal-directed reaching. I argue that sensory transformations must play a central role in any modeling effort. In particular the statistical properties of these transformations factor heavily into the way in which downstream signals are combined. As a result, our models of optimal integration are only expected to apply “locally”, i.e. independently for each brain area. I suggest that local optimality can be reconciled with globally optimal behavior if one views the collection of parietal sensorimotor areas not as a set of task-specific domains, but rather as a palette of complex, sensorimotor representations that are flexibly combined to drive downstream activity and behavior.