Wheeler Mark E, Woo Sarah G, Ansel Tobin, Tremel Joshua J, Collier Amanda L, Velanova Katerina, Ploran Elisabeth J, Yang Tianming
University of Pittsburgh.
J Cogn Neurosci. 2015 Apr;27(4):705-19. doi: 10.1162/jocn_a_00739. Epub 2014 Oct 14.
The evolution of neural activity during a perceptual decision is well characterized by the evidence parameter in sequential sampling models. However, it is not known whether accumulating signals in human neuroimaging are related to the integration of evidence. Our aim was to determine whether activity accumulates in a nonperceptual task by identifying brain regions tracking the strength of probabilistic evidence. fMRI was used to measure whole-brain activity as choices were informed by integrating a series of learned prior probabilities. Participants first learned the predictive relationship between a set of shape stimuli and one of two choices. During scanned testing, they made binary choices informed by the sum of the predictive strengths of individual shapes. Sequences of shapes adhered to three distinct rates of evidence (RoEs): rapid, gradual, and switch. We predicted that activity in regions informing the decision would modulate as a function of RoE prior to the choice. Activity in some regions, including premotor areas, changed as a function of RoE and response hand, indicating a role in forming an intention to respond. Regions in occipital, temporal, and parietal lobes modulated as a function of RoE only, suggesting a preresponse stage of evidence processing. In all of these regions, activity was greatest on rapid trials and least on switch trials, which is consistent with an accumulation-to-boundary account. In contrast, activity in a set of frontal and parietal regions was greatest on switch and least on rapid trials, which is consistent with an effort or time-on-task account.
在感知决策过程中，神经活动的演变可以通过序贯抽样模型中的证据参数得到很好的表征。然而，尚不清楚人类神经成像中累积的信号是否与证据整合有关。我们的目的是通过识别追踪概率证据强度的脑区，来确定在非感知任务中活动是否会累积。当通过整合一系列学习到的先验概率来做出选择时，功能磁共振成像（fMRI）被用于测量全脑活动。参与者首先学习一组形状刺激与两种选择之一之间的预测关系。在扫描测试期间，他们根据各个形状的预测强度总和做出二元选择。形状序列遵循三种不同的证据率（RoE）：快速、渐进和切换。我们预测，在做出选择之前，参与决策的脑区活动会根据RoE进行调节。包括运动前区在内的一些脑区的活动，会根据RoE和反应手而发生变化，这表明在形成反应意图方面发挥了作用。枕叶、颞叶和顶叶的脑区仅根据RoE进行调节，这表明处于证据处理的反应前阶段。在所有这些脑区中，快速试验时的活动最大，切换试验时的活动最小，这与累积到边界的解释一致。相比之下，一组额叶和顶叶区域的活动在切换试验时最大，在快速试验时最小，这与努力或任务持续时间的解释一致。
