视觉区域学习对未来价值驱动选择偏差的支持

Sara Jahfari, J. Theeuwes, T. Knapen
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引用次数: 6

摘要

强化学习可以使决策偏向于具有最高预期结果的选项。认知学习理论将这种偏见与纹状体和前额皮质对刺激值的持续跟踪和对选择结果的评估联系起来。然而,决策首先需要处理感官输入,到目前为止,我们对学习和感知之间的相互作用知之甚少。这项fMRI研究(N=43)将视觉BOLD反应与选择过程中的价值信念以及结果后的签名预测错误联系起来。为了理解这些在纹状体中共同发生的关系,我们通过评估在学习已经建立的单独迁移阶段对未来基于价值的决策的预测来寻求相关性。我们使用监督机器学习算法对选择结果进行解码,准确率为70%,该算法从视觉区域以及更传统的运动区域、前额叶和纹状体区域逐次进行BOLD解码。重要的是,这种对未来价值驱动的选择结果的解码再次强调了视觉活动的重要作用。这些结果提出了一种有趣的可能性,即视觉皮层对价值的跟踪支持纹状体在未来选择中倾向于更有价值的选项。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning in Visual Regions as Support for the Bias in Future Value-Driven Choice
Reinforcement learning can bias decision-making towards the option with the highest expected outcome. Cognitive learning theories associate this bias with the constant tracking of stimulus values and the evaluation of choice outcomes in the striatum and prefrontal cortex. Decisions however first require processing of sensory input, and to-date, we know far less about the interplay between learning and perception. This fMRI study (N=43), relates visual BOLD responses to value-beliefs during choice, and, signed prediction errors after outcomes. To understand these relationships, which co-occurred in the striatum, we sought relevance by evaluating the prediction of future value-based decisions in a separate transfer phase where learning was already established. We decoded choice outcomes with a 70% accuracy with a supervised machine learning algorithm that was given trial-by-trial BOLD from visual regions alongside more traditional motor, prefrontal, and striatal regions. Importantly, this decoding of future value-driven choice outcomes again highligted an important role for visual activity. These results raise the intriguing possibility that the tracking of value in visual cortex is supportive for the striatal bias towards the more valued option in future choice.
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