Computation and Neural Systems Program, California Institute of Technology, Pasadena, California, USA.
J Neurophysiol. 2011 Sep;106(3):1558-69. doi: 10.1152/jn.01051.2010. Epub 2011 Jun 22.
Prefrontal cortex has long been implicated in tasks involving higher order inference in which decisions must be rendered, not only about which stimulus is currently rewarded, but also which stimulus dimensions are currently relevant. However, the precise computational mechanisms used to solve such tasks have remained unclear. We scanned human participants with functional MRI, while they performed a hierarchical intradimensional/extradimensional shift task to investigate what strategy subjects use while solving higher order decision problems. By using a computational model-based analysis, we found behavioral and neural evidence that humans solve such problems not by occasionally shifting focus from one to the other dimension, but by considering multiple explanations simultaneously. Activity in human prefrontal cortex was better accounted for by a model that integrates over all available evidences than by a model in which attention is selectively gated. Importantly, our model provides an explanation for how the brain determines integration weights, according to which it could distribute its attention. Our results demonstrate that, at the point of choice, the human brain and the prefrontal cortex in particular are capable of a weighted integration of information across multiple evidences.
前额叶皮层长期以来一直被认为与涉及高级推理的任务有关，在这些任务中，必须做出决策，不仅要决定当前哪个刺激物得到了奖励，还要决定当前哪些刺激维度是相关的。然而，用于解决此类任务的精确计算机制仍然不清楚。我们使用功能磁共振成像（fMRI）对人类参与者进行了扫描，同时他们执行了一个层次内/外维度转移任务，以研究主体在解决高级决策问题时使用的策略。通过使用基于计算模型的分析，我们发现了行为和神经证据，表明人类并不是通过偶尔将注意力从一个维度转移到另一个维度来解决此类问题，而是同时考虑多个解释。与选择性门控注意力的模型相比，整合所有可用证据的模型可以更好地解释人类前额叶皮层的活动。重要的是，我们的模型为大脑如何根据其注意力分配来确定整合权重提供了一个解释。我们的结果表明，在选择点，人脑，特别是前额叶皮层，能够对多个证据进行加权整合信息。
