Nature Human Behaviour ( IF 29.9 ) Pub Date : 2020-12-14 , DOI: 10.1038/s41562-020-00967-9 Simon P Kelly 1, 2, 3 , Elaine A Corbett 2, 3 , Redmond G O'Connell 3
To interact successfully with diverse sensory environments, we must adapt our decision processes to account for time constraints and prior probabilities. The full set of decision-process parameters that undergo such flexible adaptation has proven to be difficult to establish using simplified models that are based on behaviour alone. Here, we utilize well-characterized human neurophysiological signatures of decision formation to construct and constrain a build-to-threshold decision model with multiple build-up (evidence accumulation and urgency) and delay components (pre- and post-decisional). The model indicates that all of these components were adapted in distinct ways and, in several instances, fundamentally differ from the conclusions of conventional diffusion modelling. The neurally informed model outcomes were corroborated by independent neural decision signal observations that were not used in the model’s construction. These findings highlight the breadth of decision-process parameters that are amenable to strategic adjustment and the value in leveraging neurophysiological measurements to quantify these adjustments.
中文翻译:
人类先验知觉决策的神经计算机制
为了与不同的感官环境成功交互,我们必须调整我们的决策过程以考虑时间限制和先验概率。事实证明,使用仅基于行为的简化模型很难建立经过如此灵活适应的全套决策过程参数。在这里,我们利用充分表征的人类决策形成的神经生理学特征来构建和约束具有多个构建(证据积累和紧迫性)和延迟组件(决策前和决策后)的构建到阈值决策模型。该模型表明,所有这些组件都以不同的方式进行了调整,并且在某些情况下,与传统扩散建模的结论根本不同。神经信息模型结果得到了模型构建中未使用的独立神经决策信号观察的证实。这些发现突出了可以进行战略调整的决策过程参数的广度,以及利用神经生理学测量来量化这些调整的价值。