Linking Perception, Cognition, and Action: Psychophysical Observations and Neural Network Modelling
Linking Perception, Cognition, and Action: Psychophysical Observations and Neural Network Modelling
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DOI：
10.1371/journal.pone.0102553
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发表时间：
2014-07-16
期刊：
影响因子：
3.7
通讯作者：
Merchant, Hugo
中科院分区：
文献类型：
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作者：
Carlos Mendez, Juan;Perez, Oswaldo;Merchant, Hugo
有人认为，感知、决策和运动规划实际上是紧密交织在一起的大脑过程。然而，它们如何在神经回路中实现仍然是一个有争议的问题。我们测试了人类受试者的时间分类任务，其中间隔被归类为短或长。受试者通过将光标移动到两个可能的目标中的一个来传达他们的决定，这两个目标在不同的试验中以不同的角度分开。虽然间隔呈现和决策沟通之间有1秒的延迟，但分类困难影响了被试的表现、反应（RT）和运动时间（MT）。此外，反应和运动时间也受到目标之间的距离的影响。这意味着，不仅知觉，而且运动相关的考虑被纳入决策过程。因此，我们寻找一个模型，可以使用分类难度和目标分离来描述受试者的表现，RT和MT。我们开发了一个由两个相互抑制的神经群组成的网络，每个神经群都被调整到一个可能的类别，并由一个积累和一个记忆节点组成。这个网络顺序地获取间隔信息，将其保存在工作记忆中，然后被吸引到两种可能的状态之一，对应于一个分类决策。它忠实地复制了受试者的RT和MT作为分类难度和目标距离的函数;它还复制了作为分类难度的函数的表现。此外，该模型被用来对未测试的持续时间，目标距离和延迟持续时间的影响作出新的预测。据我们所知，这是第一个生物学上合理的模型，已被提出来解释决策和沟通，通过整合感官和运动规划信息。
It has been argued that perception, decision making, and movement planning are in reality tightly interwoven brain processes. However, how they are implemented in neural circuits is still a matter of debate. We tested human subjects in a temporal categorization task in which intervals had to be categorized as short or long. Subjects communicated their decision by moving a cursor into one of two possible targets, which appeared separated by different angles from trial to trial. Even though there was a 1 second-long delay between interval presentation and decision communication, categorization difficulty affected subjects' performance, reaction (RT) and movement time (MT). In addition, reaction and movement times were also influenced by the distance between the targets. This implies that not only perceptual, but also movement-related considerations were incorporated into the decision process. Therefore, we searched for a model that could use categorization difficulty and target separation to describe subjects' performance, RT, and MT. We developed a network consisting of two mutually inhibiting neural populations, each tuned to one of the possible categories and composed of an accumulation and a memory node. This network sequentially acquired interval information, maintained it in working memory and was then attracted to one of two possible states, corresponding to a categorical decision. It faithfully replicated subjects' RT and MT as a function of categorization difficulty and target distance; it also replicated performance as a function of categorization difficulty. Furthermore, this model was used to make new predictions about the effect of untested durations, target distances and delay durations. To our knowledge, this is the first biologically plausible model that has been proposed to account for decision making and communication by integrating both sensory and motor planning information.